computational biology phd nyc

Computational Biology

Our interdisciplinary M.S. in Computational Biology program is designed to provide students with expertise in the leading quantitative methods underlying modern biomedical science. The program is an in-depth response to the ever-growing need for computational methods and mathematical models in processing, analyzing, and interpreting the vast amounts of biological data generated by high-throughput techniques. Computer simulations are required to understand and predict the dynamics of complex biological systems. Precision medicine, drug development, and cancer research are only a few among the many thriving fields increasingly relying on quantitative genomics, bioinformatics, and systems biology.

The M.S. in Computational Biology (MS-CB) presents a unique, rigorous training program, equipping students with theoretical understanding and practical mastery of state-of-the-art applications of computational approaches in biology and medicine. Our faculty from Weill Cornell Medicine, Sloan-Kettering Institute, and Cornell Tech are world-class leaders in computational biology research and applications.

Upon graduation, with extensive training and field-specific, curricular workshops in career development, students will be prepared to launch successful professional careers at the forefront of data analytics, bioinformatics, and computer modeling, for example in the pharmaceutical or biotech industries. Likewise, for those interested in pursuing further education in computational biology at the PhD level, this degree will attest to their preparation and enhance their competitiveness.

Our  curriculum  is highly interdisciplinary and includes training in cutting-edge bioinformatics, statistics, machine learning, computation and simulation, quantitative biology, and genomics. The training emphasizes hands-on computer labs and practical skills to prepare students for careers beyond the classroom.

Program features include:

• 18 months duration, full-time study
• cohesive interdisciplinary educational program
• individual mentored research project
• career development training

Please  see here  for a complete list of faculty

Tuition, Fees and Scholarships

Please refer to the  student services website  for program-specific details on tuition and fees. Please note that this tuition cost and fees are set for the current academic year and are subject to change.

A small number of partial scholarships are available. Applicants applying by the priority deadline are automatically considered for these merit-based scholarships.

Program Requirements

Applicants must hold a bachelor’s degree in science or engineering. Applicants must have completed undergraduate level coursework in calculus, linear algebra, probability theory or statistics, and computer programming.

We seek applications from students with diverse undergraduate degrees and welcome applications from talented individuals of all backgrounds. 

All application forms and supporting documents can be  submitted online . You will be asked to submit or upload:

• Personal Statement describing your background and specific interest in the MS-CB program.
• Résumé/C.V.
• Three letters of recommendation. Letters must be submitted electronically as instructed through the online application.
• Transcripts from all previously attended colleges and universities
• Domestic Transcripts - Unofficial transcripts from U.S. institutions may be submitted for application review. Official transcripts will be requested from accepted students prior to matriculation.
• If using WES, please select the WES Basic Course-by-Course evaluation and choose "Cornell University - Manhattan NY" as the recipient with "Weill Graduate School of Medical Sciences" as the School/Division 
• Evaluations are accepted only from  current members of the National Association of Credit Evaluation Services (NACES) . Official course-by-course evaluations are required for application review.
• $80 application fee
• Results of the General Graduate Record (GRE) examination are  optional . The Institution Code Number is 2119.
• Scores from the  Test of English as a Foreign Language (TOEFL) ,  International English Language Testing System (IELTS) , or  Duolingo English Test . Test scores are valid for two years after the test date. To see if you qualify for an exemption, see below.
• To submit your official TOEFL scores, please go to  http://www.ets.org/toefl  and request your scores to be sent to Weill Cornell Graduate School using code 2119. Please monitor your application to ensure that your scores are populated by ETS.  
• IELTS results must be submitted directly via e-delivery to “Weill Cornell Graduate School of Medical Sciences.”
• Results for the Duolingo English Test, applicants must submit their results directly through Duolingo to “Weill Cornell Graduate School of Medical Sciences".

Application Timeline & Deadlines

The application site for Fall 2024 admission is closed. 

We are still accepting applications for the Fall 2024 class. We are operating with a rolling admissions process at this point and encourage you to submit your application as early as possible to avoid potential seat capacity or timing restrictions.  

Final deadline for applications: May 1, 2024. 

English Language Proficiency Exam Exemptions

The English language proficiency requirement may be waived if an applicant meets at least one of the following criteria:

• Citizenship/Permanent Residency
• If the applicant is a citizen or permanent resident of the United States or its territories (e.g., Puerto Rico), or a citizen of the United Kingdom, Ireland, Australia, New Zealand, or Canada, they are exempt.
• Applicants who are citizens of all other countries, including India, Pakistan, the Philippines, Hong Kong, Singapore, etc. are not exempt and must submit English language proficiency exam scores.
• English-Language Instruction
• Applicants who, at the time of enrollment, have studied in full-time status for at least two academic years within the last  five  years in the United States, the United Kingdom, Ireland, Australia, or New Zealand, or with English language instruction in Canada or South Africa, are exempt.
• Applicants must submit a transcript that shows they studied in one of the approved locations, and that the academic program was at least two years in length.
• Even if English was the language of instruction of the course or institution, it must have been in one of the eligible locations, otherwise the applicant is not exempt from the requirement.

Prospective Student Events

We're always working on putting events together. Be sure to check back soon for more event listings.

Faculty Stories

• Aguiar-Pulido, Vanessa
• Bao, Zhirong
• Bendall, Matthew
• Berger, Michael
• Betel, Doron
• Brady, Nicholas
• Christini, David
• Davis, Melissa
• Dundar, Friederike
• Elemento, Olivier
• Hajirasouliha, Iman
• Imielinski, Marcin
• Kentsis, Alex
• Khurana, Ekta
• Krogh-Madsen, Trine
• Krumsiek, Jan
• Landau, Dan
• Laughney, Ashley
• Lee, Guinevere
• Leslie, Christina
• Mason, Christopher
• Nixon, Douglas
• Papaemmanuil, Elli
• Sboner, Andrea
• Schultz, Nikolaus
• Skrabanek, Luce
• Tilgner, Hagen
• Ventura, Andrea

Courses and Required Curricular Components

• Analysis of Next-Generation Sequencing Data
• Career Development in Computational Biology
• Cellular and Molecular Biology
• Computational Biology Research
• Data Structures and Algorithms for Computational Biology
• Dynamic Models in Biology
• Functional Interpretation of High-Throughput Data
• MS-CB Thesis Research
• MS-CB Thesis Research Exploration 1&2
• Quantitative Genomics and Genetics

Student Stories

I have enjoyed exploring a bunch of different areas of research, specifically those to which I was completely new. Everyone here has been extremely supportive and there has been a lot of room for growth. Overall it's been really fun figuring out what I'd like to do moving forward!

Weill Cornell is unique in how focused it is on medical science research. There is no other institution where I can so easily find professors to collaborate with for clinical research. In the short time I have spent in the program, I have meaningfully contributed to several projects that will be published.

Student Handbook

To view the MSCB Student Handbook, click here .

  Contact Information

  Trine Krogh-Madsen, PhD, Director 413 E. 69th St, Box 190 New York, NY 10065 (646) 962 - 5392 [email protected]

Sarah Schaller, Program Coordinator 1300 York Ave, Box 65 New York, NY 10065 [email protected]

Weill Cornell Medicine Graduate School of Medical Sciences 1300 York Ave. Box 65 New York, NY 10065 Phone: (212) 746-6565 Fax: (212) 746-8906

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Computational biology ph.d. (ithaca), field of study.

Computational Biology

Program Description

Computation has become essential to biological research. Genomic databases, protein databanks, MRI images of the human brain, and remote sensing data on landscapes contain unprecedented amounts of detailed information that are transforming almost all of biology. The computational biologist must have skills in mathematics and computation as well as in biology. A key goal in training is to develop the ability to relate biological processes to computational models.   The field provides interdisciplinary training and research opportunities in a range of subareas of computational biology involving topics such as DNA and protein databases, protein structure and function, computational neuroscience, biomechanics, population genetics, and management of natural and agricultural systems. Students majoring in computational biology are expected to obtain a broad, interdisciplinary knowledge of fundamental principles in biology, computational science, and mathematics. But because the field covers a wide range of areas, it would be unrealistic to expect a student to master each facet in detail. Instead, students choose from specific subareas of study: they are expected to develop competence in at least one specific subdomain of biology (i.e., genetics, macromolecular biology, cellular biology, organismal biology, behavioral biology or ecology) and in relevant subareas of computational science and mathematics.  Students are supervised by field faculty drawn from sixteen departments.

Contact Information

102 Weill Hall Cornell University Ithaca, NY  14853

Concentrations by Subject

• computational behavioral biology
• computational biology
• computational cell biology
• computational ecology
• computational genetics
• computational macromolecular biology
• computational organismal biology

Visit the Graduate School's Tuition Rates page.

Application Requirements and Deadlines

Requirements Summary:

Please see the field's Ph.D. program page .

Learning Outcomes

Fundamentals: Demonstrated mastery of fundamental concepts, theory, and methodology in areas of biology, computer science, and mathematics relevant to the chosen specialty.

Breadth: Demonstrated broad knowledge of theory and research across several sub-disciplines in computational biology.

Originality: Demonstrated the ability to independently conduct, document, and defend original research having the potential to produce new biological insights and/or improved computational methods.

Communication: Demonstrated proficiency in oral and written presentation of results appropriate for a career in advanced research in government or industry, or advanced research and/or teaching at a college or university.

Literacy and Outreach: Demonstrated broad knowledge of the scientific literature relevant to the specialty area, including awareness of recent advances, active areas of research, and open questions. Students should also have demonstrated the ability to participate in the broader research community outside of Cornell, through meetings, conferences, individual collaborations, or other interactions.

Ethics: Demonstrated the ability to follow established ethical standards for the field, pertaining to topics such as (but not limited to) recognition of prior scholarship, acknowledgment of intellectual and material contributions to research, falsification of data, appropriate handling of human and animal subjects and of hazardous materials, and respectful and fair treatment of students and co-workers of diverse backgrounds.

Teaching: (For those entering a teaching profession) Demonstrated the ability to communicate complex idea and methods in terms students can understand, to grade and comment effectively on student work, to lead discussions effectively, and to plan an effective course in the field.

Career Progress: Demonstrated significant progress toward future career goals, or found employment, if desired.

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Computational Biology

Computational Biology Program

The computational biology ph.d. program is training the next generation of computational scientists to tackle research using the big genomic, image, remote sensing, clinical, and real world data that are transforming the biological sciences..

The graduate field of Computational Biology offers Ph.D. degrees in the development and application of data-analytical and theoretical methods, mathematical modeling and computational simulation techniques to the study of biological systems.

Computation has become essential to biological research. Genomic databases, protein databanks, MRI images of the human brain, and remote sensing data on landscapes contain unprecedented amounts of detailed information that are transforming almost all of biology. The computational biologist must have skills in mathematics and computation as well as in biology. A key goal in training is to develop the ability to relate biological processes to computational models.

The field provides interdisciplinary training and research opportunities in a range of subareas of computational biology including comparative and functional genomics, systems biology, molecular and protein networks, population genomics and genetics, bioinformatics, model system genomics, agricultural genomics, and medical genomics.

Students majoring in computational biology are expected to obtain a broad, interdisciplinary knowledge of fundamental principles in biology, computational science, and mathematics. But because the field covers a wide range of areas, it would be unrealistic to expect a student to master each facet in detail. Instead, students choose from specific subareas of study: They are expected to develop competence in at least one specific subdomain of biology and in relevant subareas of computational science and mathematics.

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Program Contacts

Associate Professor

• (607) 255-3984
• pm544 [at] cornell.edu

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• (607) 255-5488
• jf633 [at] cornell.edu

Computational and Systems Biology PhD Program

Computational and systems biology.

The field of computational and systems biology represents a synthesis of ideas and approaches from the life sciences, physical sciences, computer science, and engineering. Recent advances in biology, including the human genome project and massively parallel approaches to probing biological samples, have created new opportunities to understand biological problems from a systems perspective. Systems modeling and design are well established in engineering disciplines but are newer in biology. Advances in computational and systems biology require multidisciplinary teams with skill in applying principles and tools from engineering and computer science to solve problems in biology and medicine. To provide education in this emerging field, the Computational and Systems Biology (CSB) program integrates MIT's world-renowned disciplines in biology, engineering, mathematics, and computer science. Graduates of the program are uniquely prepared to make novel discoveries, develop new methods, and establish new paradigms. They are also well-positioned to assume critical leadership roles in both academia and industry, where this field is becoming increasingly important.

Computational and systems biology, as practiced at MIT, is organized around "the 3 Ds" of description, distillation, and design. In many research programs, systematic data collection is used to create detailed molecular- or cellular-level descriptions of a system in one or more defined states. Given the complexity of biological systems and the number of interacting components and parameters, system modeling is often conducted with the aim of distilling the essential or most important subsystems, components, and parameters, and of obtaining simplified models that retain the ability to accurately predict system behavior under a wide range of conditions. Distillation of the system can increase the interpretability of the models in relation to evolutionary and engineering principles such as robustness, modularity, and evolvability. The resulting models may also serve to facilitate rational design of perturbations to test understanding of the system or to change system behavior (e.g., for therapeutic intervention), as well as efforts to design related systems or systems composed of similar biological components.

CSB Faculty and Research

More than 70 faculty members at the Institute participate in MIT's Computational and Systems Biology Initiative (CSBi). These investigators span nearly all departments in the School of Science and the School of Engineering, providing CSB students the opportunity to pursue thesis research in a wide variety of different laboratories. It is also possible for students to arrange collaborative thesis projects with joint supervision by faculty members with different areas of expertise. Areas of active research include computational biology and bioinformatics, gene and protein networks, regulatory genomics, molecular biophysics, instrumentation engineering, cell and tissue engineering, predictive toxicology and metabolic engineering, imaging and image informatics, nanobiology and microsystems, biological design and synthetic biology, neurosystems biology, and cancer biology.

The CSB PhD Program

The CSB PhD program is an Institute-wide program that has been jointly developed by the Departments of Biology, Biological Engineering, and Electrical Engineering and Computer Science. The program integrates biology, engineering, and computation to address complex problems in biological systems, and CSB PhD students have the opportunity to work with CSBi faculty from across the Institute. The curriculum has a strong emphasis on foundational material to encourage students to become creators of future tools and technologies, rather than merely practitioners of current approaches. Applicants must have an undergraduate degree in biology (or a related field), bioinformatics, chemistry, computer science, mathematics, statistics, physics, or an engineering discipline, with dual-emphasis degrees encouraged.

CSB Graduate Education

All students pursue a core curriculum that includes classes in biology and computational biology, along with a class in computational and systems biology based on the scientific literature. Advanced electives in science and engineering enhance both the breadth and depth of each student's education. During their first year, in addition to coursework, students carry out rotations in multiple research groups to gain a broader exposure to work at the frontier of this field, and to identify a suitable laboratory in which to conduct thesis research. CSB students also serve as teaching assistants during one semester in the second year to further develop their teaching and communication skills and facilitate their interactions across disciplines. Students also participate in training in the responsible conduct of research to prepare them for the complexities and demands of modern scientific research. The total length of the program, including classwork, qualifying examinations, thesis research, and preparation of the thesis is roughly five years.

The CSB curriculum has two components. The first is a core that provides foundational knowledge of both biology and computational biology. The second is a customized program of electives that is selected by each student in consultation with members of the CSB graduate committee. The goal is to allow students broad latitude in defining their individual area of interest, while at the same time providing oversight and guidance to ensure that training is rigorous and thorough.

Core Curriculum

The core curriculum consists of three classroom subjects plus a set of three research rotations in different research groups. The classroom subjects fall into three areas described below.

Modern Biology (One Subject): A term of modern biology at MIT strengthens the biology base of all students in the program. Subjects in biochemistry, genetics, cell biology, molecular biology, or neurobiology fulfill this requirement. The particular course taken by each student will depend on their background and will be determined in consultation with graduate committee members.

Computational Biology (One Subject): A term of computational biology provides students with a background in the application of computation to biology, including analysis and modeling of sequence, structural, and systems data. This requirement can be fulfilled by 7.91[J] / 20.490[J] Foundations of Computational and Systems Biology.

Topics in Computational and Systems Biology (One Subject): All first-year students in the program participate in / 7.89[J] Topics in Computational and Systems Biology, an exploration of problems and approaches in the field of computational and systems biology through in-depth discussion and critical analysis of selected primary research papers. This subject is restricted to first-year PhD students in CSB or related fields in order to build a strong community among the class. It is the only subject in the program with such a limitation.

Research Group Rotations (Three Rotations): To assist students with lab selection and provide a range of research activities in computational and systems biology, students participate in three research rotations of one to two months' duration during their first year. Students are encouraged to gain experience in experimental and computational approaches taken across different disciplines at MIT.

Advanced Electives

The requirement of four advanced electives is designed to develop both breadth and depth. The electives add to the base of the diversified core and contribute strength in areas related to student interest and research direction. To develop depth, two of the four advanced electives must be in the same research area or department. To develop breadth, at least one of the electives must be in engineering and at least one in science. Each student designs a program of advanced electives that satisfies the distribution and area requirements in close consultation with members of the graduate committee.

Additional Subjects: As is typical for students in other doctoral programs at MIT, CSB PhD students may take classes beyond the required diversified core and advanced electives described above. These additional subjects can be used to add breadth or depth to the proposed curriculum, and might be useful to explore advanced topics relevant to the student's thesis research in later years. The CSB Graduate Committee works with each graduate student to develop a path through the curriculum appropriate for his or her background and research interests.

Training in the Responsible Conduct of Research: Throughout the program, students will be expected to attend workshops and other activities that provide training in the ethical conduct of research. This is particularly important in interdisciplinary fields such as computational and systems biology, where different disciplines often have very different philosophies and conventions. By the end of the fourth year, students will have had about 16 hours of training in the responsible conduct of research.

Qualifying Exams: In addition to coursework and a research thesis, each student must pass a written and an oral qualifying examination at the end of the second year or the beginning of the third year. The written examination involves preparing a research proposal based on the student's thesis research, and presenting the proposal to the examination committee. This process provides a strong foundation for the thesis research, incorporating new research ideas and refinement of the scope of the research project. The oral examination is based on the coursework taken and on related published literature. The qualifying exams are designed to develop and demonstrate depth in a selected area (the area of the thesis research) as well as breadth of knowledge across the field of computational and systems biology.

Thesis Research: Research will be performed under the supervision of a CSBi faculty member, culminating in the submission of a written thesis and its oral defense before the community and thesis defense committee. By the second year, a student will have formed a thesis advisory committee that they will meet with on an annual basis.

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PhD & MD/PhD Education

Memorial Sloan Kettering is dedicated to the advancement of our understanding of the biomedical sciences. An essential component of that mission is the education of tomorrow’s scientific leaders. To train the next generation of biomedical researchers, MSK’s graduate educational programs offer a unique and comprehensive program in the study of biomedical sciences and the management of cancer. This includes graduate PhD programs in cancer biology and cancer engineering that offer opportunities to learn from basic scientists and oncologists, as well as an MD/PhD program. Detailed descriptions of each, complete with application information, can be found at each of the programs’ websites. 

Gerstner Sloan Kettering Graduate School of Biomedical Sciences Learn about the Cancer Biology and Cancer Engineering PhD programs, research faculty, admission process, and campus life at our Gerstner Sloan Kettering Graduate School of Biomedical Sciences.

PhD Programs in Computational Biology & Medicine The Tri-Institutional Program in Computational Biology and Medicine is a collaborative effort among Memorial Sloan Kettering Cancer Center, Cornell University in Ithaca, and Weill Cornell Medical College. Our training prepares researchers for careers at the interface between computer science and biology.

PhD Program in Chemical Biology The Tri-Institutional PhD Program in Chemical Biology is a joint graduate program offered by Memorial Sloan Kettering Cancer Center, Weill Cornell Medical College, and the Rockefeller University that trains students to use chemical approaches to address problems at the forefront of biomedical research.

Weill Cornell Graduate School of Medical Sciences A collaboration between the Weill Cornell Medical College and the Sloan Kettering Institute, our school trains future generations of biomedical researchers.

MD/PhD Program Sponsored collectively by the Sloan Kettering Institute, The Rockefeller University, and Weill Cornell Medical College, the Tri-Institutional MD/PhD Program trains physician-scientists to become leaders in biomedical research.

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Tri-Institutional Training Program in Computational Biology and Medicine (CBM)

The CBM program brings together the exceptional educational and research resources of Cornell University in Ithaca, its Medical College in NYC (Weill Cornell Medical College), and Memorial Sloan-Kettering Cancer Center. Program faculty, representing a wide range of research disciplines, provide CBM students with the full range of training opportunities… more

Physiology, Biophysics and Systems Biology (PBSB)

The PBSB program focuses on analyzing and explaining the functions of the human body’s building blocks (cells, tissues and organs), as well creating a systems-level view of function in physiological components (e.g., from the cell to the heart, and from the neuron to the nervous system)… more

Tri-Institutional PhD Program in Chemical Biology (TPCB)

The TPCB program focuses on research and training at the interface of chemistry and biology. Students choose from a broad range of chemical biology research areas based on their skills and interests, from organic synthesis of bioactive small molecules, to mechanistic investigations of macromolecules… more

Tri-Institutional MD-PhD Program (MDPHD)

The aim of the MD-PhD program is to educate biomedical investigators who, motivated by the intellectual challenges of disease, will lead the quest for new biomedical discoveries. The program offers a rigorous, yet flexible, specially tailored course of study and unrestricted access to experienced mentors in leading research laboratories… more

Neuroscience

The Neuroscience PhD program examines the development and function of the nervous system from a wide variety of scientific disciplines, including molecular genetics, biochemistry, pharmacology, neuroanatomy, electrophysiology, and computational and systems neuroscience… more

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Graduate Programs

Computational biology.

The Center for Computational Molecular Biology (CCMB) offers Ph.D. degrees in Computational Biology to train the next generation of scientists to perform cutting edge research in the multidisciplinary field of Computational Biology.

During the course of their Ph.D. studies students will develop and apply novel computational, mathematical , and statistical techniques to problems in the life sciences. Students in this program must achieve mastery in three areas - computational science, molecular biology, and probability and statistical inference - through a common core of studies that spans and integrates these areas.

The Ph.D. program in Computational Biology draws on course offerings from the disciplines of the Center’s Core faculty members. These areas are Applied Mathematics, Computer Science, the Division of Biology and Medicine, the Center for Biomedical Informatics, and the School of Public Health. Our faculty and Director of Graduate Studies work with each student to develop the best plan of coursework and research rotations to meet the student’s goals in their research focus and satisfy the University’s requirements for graduation.

Applicants should state a preference for at least one of these areas in their personal statement or elsewhere in their application. In addition, students interested in the intersection of Applied Mathematics and Computational Biology are encouraged to apply directly to the  Applied Mathematics Ph.D. program , and also to contact relevant  CCMB faculty members .

Our Ph.D. program assumes the following prerequisites: mathematics through intermediate calculus, linear algebra and discrete mathematics, demonstrated programming skill, and at least one undergraduate course in chemistry and in molecular biology. Exceptional strengths in one area may compensate for limited background in other areas, but some proficiency across the disciplines must be evident for admission.

Additional Resources

CCMB computing resources include a set of multiprocessor computer clusters and data storage servers with 392 processors. The CCMB Cluster is the largest dedicated computing system on campus for computational biology and bioinformatics applications. See also answers to  frequently asked questions .

Application Information

Application requirements, gre subject:.

Not required

GRE General:

Personal statement:.

Applicants will be asked a series of short form questions regarding their interest in computational biology, their research experiences, and their goals for the future. 1) Describe the life experiences that inspired you to pursue a career in science. 2) Describe at least one research experience you have had that prepared you intellectually/ scientifically for a career in computational biology. 3) Explain at least one challenge you have overcome in life or research to pursue a scientific career and what you have learned from this experience. 4) Why would you like to pursue your PhD in the Brown CCMB program? (Include at least two faculty members who you would like to work with at Brown and why.) 5) Discuss how you aspire to contribute to our mission to promote diversity and inclusion through your research, teaching, or service.

Dates/Deadlines

Application deadline, completion requirements.

Six graduate–level courses, two eight–week laboratory rotations, preliminary research presentation, dissertation, oral defense

Contact and Location

Center for computational molecular biology, location address, mailing address.

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Bioinformatics, M.S.

Request more information   apply   faq, become a bioinformatics leader.

Revolutionary changes are taking place in how we interpret health and treat disease. With extraordinary advances in both gene sequencing and machine learning, the bioinformatics field is expanding exponentially and creating a myriad of opportunities for professionals with in-depth knowledge of techniques for mastering complex data.

In NYU Tandon’s Bioinformatics Master of Science program , you will build strong skills in molecular biology and big data analysis. Develop solutions to critical challenges throughout medicine and the life sciences by learning to utilize genomic information and next generation sequence analysis tools.

By creating and advancing algorithms, utilizing computational and statistical techniques, and applying theory, you can solve practical problems that arise in the management of biological data. Prepare to make significant contributions to society through groundbreaking innovations in cancer care, vaccine design, agriculture, and energy.

What Is Bioinformatics?

Bioinformatics is a rapidly growing discipline of science that applies computation and analysis techniques to the collection and interpretation of biology-related data. There is a strong demand for professionals with an advanced education in molecular biology, statistics, programming, machine learning, and sequence and pathway analysis.

Upon completing your bioinformatics degree, you will be well qualified to address important issues in areas such as infectious diseases, public health, genetic diseases, agriculture, and green technology.

Why Choose NYU Tandon?

At NYU Tandon, we are educating and nurturing tomorrow’s biotech rock stars. As a student in our flexible 30-credit program, you will develop the refined skill set necessary for a successful career in bioinformatics and computational biology. Prepare to make an impact on vital challenges such as Alzheimer’s, autism, diabetes, obesity, genetically modified organisms (GMO), and greenhouse gas sequestration.

• Learn about  Bioinformatics Admission Requirements .
• Learn about  General Admission Requirements .

Capstone Project

At least three credits of Capstone course (BI- GY 810X BIOINFORMATICS CAPSTONE) are required to fulfill the M.S. Bioinformatics requirement for graduation. This is a variable credit course from 3cr to 9crs. Which means that you can take it for three or if you have six credits remaining you can take it for the six.

Industry internships can count as capstone credits, but the student has to register for capstone BI-810X. If it meets the programs capstone criteria, significant programming component(Python, R, and/Shell scripting). The agreement is formalized between us and the manager/PI. We avoid all agreements that deal with proprietary data.

Students must find the internships themselves (although we will help).

Projects often deal with NGS analysis. Basically, the student demonstrates their skills in a live environment.

Most of our relationships are with academic labs. We don't get involved  in legal issues concerning IP.

Completion of:

• Problem Solving
• Applied biostatistics

There are several labs with multiple projects that we work with. We can place students in any of them.

Preparatory Course

The NYU Tandon Bridge  course is recommended to those interested in a Bioinformatics master's degree who are lacking a Bioinformatics degree or other substantial related experience.

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Applying to the PhD Program

Phd program admissions.

We believe our PhD program is unique with respect to the breadth of research topics, the training in quantitative, cutting-edge biology methods, our funding structure, and the role our students play in the Department.

If you like to apply, we encourage you to visit our Graduate Resource Guide for detailed information on the program and application requirements.

Submitting Your Application

To submit an application to the Biology PhD program, please read carefully the information in the GSAS Application Resource Center , and then click here to proceed to the online application - PhD Program Application

The deadline for PhD applications is December 1.

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Please visit our  Graduate Financial, Insurance and Housing Information page to learn more about financial assistance for PhD students.

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Computational Cell Biology, Anatomy and Pathology PhD

Jacobs school of medicine and biomedical sciences, program description.

The Computational Cell Biology, Anatomy and Pathology PhD program is a unique connector between the basic and clinical sciences. New technology has enabled tools for examination of biological structure in both macroscopic and microscopic worlds, and has facilitated powerful computational approaches for integrating those data with other modes including molecular, genetic, and biochemical information. Imaging, mechanical, electrical and optical biosensors, and high-resolution tissue and cellular microscopic evaluations, can be married with the new analytics of machine vision and machine learning to obtain insight into biomedical mechanisms.

John Kolega 955 Main St., Room 4258 Buffalo, NY 14203 Email: [email protected] Phone: 716-829-3527 Fax: 716-829-2725

Instruction Method

• In Person   (100 percent of courses offered in person)

Full/Part Time Options

Credits required, time-to-degree.

• 3 to 5 Years

Application Fee

This program is officially registered with the New York State Education Department (SED).

• Pathology and Anatomical Sciences >
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• Computational Cell Biology, Anatomy and Pathology (PhD)

Computational Cell Biology, Anatomy, and Pathology (PhD)

Briana Santo Doctoral student in computational cell biology, anatomy and pathology

The Department of Pathology & Anatomical Sciences offers a program of course work and research training leading to the degree of Doctor of Philosophy in Computational Cell Biology, Anatomy and Pathology.

This program prepares students for the frontiers of modern medical research by training them to evaluate, communicate, and create knowledge of biological structure and the role of that structure in the function of cells and organisms, with an emphasis on incorporating computational and engineering methods with clinical medicine and human biology.

Our PhD program in Computational Cell Biology, Anatomy and Pathology aims to produce scientists with knowledge of biological principles at all levels of scale and who are enabled by proficiency in computational imaging methodologies and data analyses.

Research by our faculty employs biological imaging, genetics, and cellular, molecular and biochemical analyses to examine normal and abnormal biological function in a range of organ systems.  Data from these varied approaches can be aligned with computational tools in order to gain novel insights into very complex phenomena and yield new understanding of disease mechanisms.

We offer state-of-the-art instruction in both the biological principles and the quantitative methodologies, with particular strength in microscopy and the analysis of biological form and function.

Brandon Ginley, PhD ’21 Computational cell biology, anatomy and pathology 

The Doctoral Degree Program

Our faculty are engaged in research in cell and developmental biology, systems biology and informatics, bioimaging, and neuroscience.

Research projects tend to be highly interdisciplinary, with faculty collaborations in the Canon Stroke & Vascular Research Center , Roswell Park Comprehensive Cancer Center , and the Departments of Computer Science , Electrical Engineering , Materials Design and Innovation , and Mechanical Engineering , as well as other departments within the Jacobs School of Medicine and Biomedical Sciences. To accommodate such diverse interactions, prescribed coursework is kept at a minimum, and it is the advisor's responsibility to arrange with the student an appropriately tailored program of study.

The program for each student is developed on an individual basis but, in general, comprises interdisciplinary courses, courses in areas relevant to the student's research, and a substantial thesis prepared under the supervision of a full time department faculty member and committee selected by the student and faculty advisor.

Academic Requirements

The core curriculum consists of the following courses:

• Graduate Seminar
• Cell Biology
• Form, Function and Visualization of Human Gross Anatomy or Quantitative Neuroanatomy
• Microscopic Anatomy with an Introduction to Computational Methods
• General Pathology Introduction
• Microscopic Image Acquisition
• Biomedical Pattern Analysis and Machine Learning
• Additional coursework is at the discretion of the student and her/his thesis advisor.

Steven A. Lewis Doctoral student in computational cell biology, anatomy and pathology

Qualifying Examination

In addition to coursework, a qualifying examination is required of all students in the PhD program. The qualifying exam is intended to prepare a student for carrying out independent research.  It consists of the presentation and defense of a proposal in two phases: a written description of the project in the style of an NIH or NSF grant proposal, and a formal oral presentation of the proposal to the program faculty.  Because designing experiments, effectively describing one’s ideas, and making persuasive arguments in writing and in person represent essential skills for any scientist, preparing for this exam is a key component of graduate training.

Dissertation Research

A written dissertation based on the research shall be submitted to the dissertation committee, at least three weeks before the scheduled defense. After the research defense, the student must submit one unbound copy of the dissertation to the Graduate School and one bound copy to the Department, arranged in the format required by the Graduate School. The departmental copy must be submitted before the Graduate School copies are submitted.

Dissertation Defense

The definitive component of the PhD degree is the dissertation.  Although we have a relatively small faculty, a very diverse range of topics are studied in our department, and students dissertations can focus on any of a wide variety of subjects.

Director of Graduate Studies

John Kolega, Ph.D.

Associate Professor / Graduate Program Director

Department of Pathology & Anatomical Sciences Jacobs School Room 4258 955 Main St Buffalo, NY 14203

Phone: (716) 829-3527; Fax: (716) 829-2725

Email: [email protected]

Joint Carnegie Mellon-University of Pittsburgh Ph.D. Program in Computational Biology

Carl kingsford elected 2024 iscb fellow, similar genetic elements underlie vocal learning in mammals, logan and pfenning labs publish in nature communications, cpcb faculty and students win first place in cache challenge.

The Joint   C MU- P itt Ph.D. Program in   C omputational   B iology (CPCB)    provides interdisciplinary training in using quantitative and computational approaches to tackle scientific questions that lie at the interface of the life, physical, engineering, and computer sciences.  CPCB trainees are taught and mentored by leading experts at two of the foremost computer science and biomedical research institutions in the world.

The program provides students with interdisciplinary training in various fields of computational biology: Cellular and Systems Modeling, Computational Structural Biology, Bioimage Informatics, and Computational Genomics.  CPCB students also benefit from numerous professional development opportunities available at both host institutions.  Together, the CPCB program positions our students to be leaders in this exciting field of biology and has prepared our graduates to go on to successful careers in both academia, industry, and beyond!

The program currently has 91 students, who are taught and mentored by leading experts at two of the foremost computer science and biomedical research institutions in the world. Students receive interdisciplinary training from 57 core faculty and 57 affiliated faculty, representing over 30 departments and centers in the universities.