Computational Biology Ph.D. (Ithaca)
Field of Study
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 InformationWebsite: https://compbio.cornell.edu/
Phone: (607) 255-5488
102 Weill Hall
Ithaca, NY 14853
Concentrations by Subject
- computational behavioral biology
- computational biology
- computational cell biology
- computational ecology
- computational genetics
- computational macromolecular biology
- computational organismal biology
Application Requirements and Deadlines
Please see the field's Ph.D. program page.
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.