Computational Biology Ph.D. (Ithaca)
Field of Study
Program Description
Modern biology has transformed into a data-driven science, where the scale and complexity of biological information (from sequences to structures to images to remote sensing data) produced from emerging technologies now demands sophisticated computational approaches to gain new insights into biological processes. While essentially every biologist must be quantitatively trained in this era, computational biology is recognized as a distinct discipline owing to its emphasis on advancing the computational, mathematical, and statistical frontier while also making progress on important biological problems. Computational biologists are thus necessarily interdisciplinary and training and research in the field reflects that. Students in the field will focus on quantitative challenges in one of a range of topics including sequence analysis, protein structure and function, computational neuroscience, systems biology, evolutionary genetics, and the management of natural and agricultural systems. Students are supervised by field faculty drawn from eighteen academic units across the Ithaca and New York City campuses.
Contact Information
Website: https://cals.cornell.edu/computational-biologyEmail: compbio@cornell.edu
Phone: (607) 255-5488
401 Atkinson 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
Tuition
Visit the Graduate School's Tuition Rates page.
Application Requirements and Deadlines
Application Deadlines:
Dec. 1
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.