Computational biology PhD programs sit at the intersection of biological sciences and computer science. These programs train students to analyze biological systems and processes using computational methods.
Obtaining a PhD in computational biology can open up careers in research, teaching, industry, and more But getting accepted into top programs requires extensive preparation and a competitive application.
In this guide, we’ll walk through the key steps needed to apply successfully to PhD programs in computational biology. Follow these tips to maximize your chances and launch your career in this fast-growing field.
What is Computational Biology?
Computational biology utilizes computer science, mathematics, statistics, physics, and engineering to study biology. Researchers in the field develop and apply algorithms, models, simulations, and other computational techniques to analyze complex biological data and systems.
Some common focus areas include:
- Bioinformatics – Using data mining on biological data like genomic and proteomic sequences
- Modeling – Creating mathematical and computational models of biological processes and systems
- Imaging – Processing and analyzing images from medical scanning and microscopy
- Simulation – Modeling 3D protein structures, biological networks, organism development, and other processes via simulation
A PhD trains students to conduct original research and independent study in these and other computational biology subfields,
Why Get a PhD in Computational Biology?
There are many compelling reasons to pursue a PhD in computational biology:
- Conduct groundbreaking research mixing life sciences and computer science
- Develop expertise in highly valued computational skills like data mining, modeling, and simulation
- Work in exciting industries like genomics, biotechnology, and medical imaging
- Collaborate with top scientists and access cutting-edge labs
- Teach computational biology at universities after graduating
- Leverage the degree for senior roles in biotech and pharmaceutical companies
- Tackle challenging problems with huge potential societal impact
A PhD in computational biology unlocks a world of opportunity in science and private industry.
Key Steps to Apply for PhD Programs
Applying for competitive PhD programs in computational biology includes these key steps:
1. Research Programs
Explore programs that align with your research interests. Gather details on curriculum, research groups, and potential advisors from websites. Create a target list of ideal programs.
2. Obtain Research Experience
Programs want candidates with proven research skills. Seek undergraduate research fellowships, summer research programs, or lab technician roles to gain robust hands-on experience.
3. Consider a Master’s
Many applicants have a master’s degree already. One may help strengthen your background knowledge and improve candidacy.
4. Understand Requirements
Check each program’s prerequisites, GRE scores, statement prompts, recommendations required, and other application specifications.
5. Research Funding
Look into fellowships, teaching assistantships, and other funding options to cover costs and provide stipends while in the program.
6. Submit Applications
Work closely with recommenders and mentors to submit polished applications that paint you as a promising researcher,
We’ll now explore each step in more detail.
Research Programs Thoroughly
Dedicate time up front to thoroughly research potential PhD programs in computational biology. Identify ones doing innovative research aligned with your specific interests and goals.
Look for:
- Cutting-edge labs conducting studies you want to join
- Interdisciplinary curriculum combining life sciences, computer science, statistics, math
- Globally recognized faculty driving major advances in the field
- Strong mentoring, professional development, and networking
- Sufficient stipends, fellowships, and funding opportunities
Create a spreadsheet to track details on reach program. Save notes on each after exploring websites, current research, and more.
Obtain Extensive Hands-On Research Experience
Admissions committees want to see candidates with deep research experience appropriate to the program. This proves you have the required skills and potential for high-level studies.
Ways to build a strong research background include:
- Completing undergraduate research fellowships and training programs
- Working in campus labs doing computational biology projects
- Participating in summer undergraduate research programs like REUs
- Working as a lab technician or research assistant after college
- Taking a year off to do full-time research before applying
Stack up as much direct experience as possible with computational analysis methods applied to biological questions.
Earn a Master’s Degree (Optional but Recommended)
While not absolutely required, having a Master’s degree gives applicants a leg up for PhD programs. A Master’s enables you to:
- Establish greater research experience
- Demonstrate potential for advanced studies
- Expand knowledge in focused topics
- Improve academic writing and analysis skills
- Get strong recommendation letters from thesis advisors
A thesis-based Master’s where you conduct rigorous independent research boosts your PhD candidacy significantly.
Understand Application Requirements Thoroughly
Carefully review all application requirements for each target program:
- GPA cutoffs and course prerequisites
- GRE general test scores and biology/biochem subject test scores
- Personal statements and research statements detailing experience, interests, and goals
- 2-3 recommendation letters speaking to research potential
- Application forms, transcripts, and supplemental essays or questionnaires
- Application fees and submission process
Thoroughly understanding requirements prevents critical mistakes or omissions that could sink your application.
Research Funding Options Extensively
PhD programs in computational biology take 4-6 years to complete. You need funding to cover tuition and provide a stipend for living costs throughout.
Some options to research thoroughly include:
- Teaching assistantships offered by the department
- University fellowships and grants for STEM PhDs
- External fellowships like NSF GRFP and NIH F31 awards
- Industry sponsorships and internships
- Research assistantships working on faculty projects
- Loans and savings
- Applying for individual advisor/lab funding once enrolled
Having a plan to fund this multi-year degree is essential.
Submit Polished Applications and Interview Strongly
Allow plenty of time to perfect each component of your PhD program applications. Follow instructions closely and craft materials that paint you as a driven, curious researcher with immense potential.
If invited for admissions interviews, prepare extensively so you can convey your experience, interests, and goals persuasively. Use interviews to make a strong impression on faculty.
With dedication and smart preparation, you can get accepted to excellent PhD programs that empower your career in computational biology research and beyond.
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 MITs 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 MITs 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 informatics, nanobiology and microsystems, biological design and synthetic biology, neurosystems biology, and cancer biology.
Genome bioinformatics: can you build expertise from scratch? | Lilit Nersisyan | TEDxYerevan
Where can I get a PhD in computational biology?
Under the auspices of the Center for Computational Biology, the Computational Biology Graduate Group offers the PhD in Computational Biology as well as the Designated Emphasis in Computational and Genomic Biology, a specialization for doctoral students in associated programs.
How long does it take to get a PhD in computational biology?
Many of these faculty are available as potential dissertation research advisors for Computational Biology PhD students, with more available for participation on doctoral committees. The time to degree (normative time) of the Computational Biology PhD is five years.
What is computational biology?
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.
Does computational biology offer a master’s degree?
Admission for the Computational Biology PhD is for the fall semester only, and Computational Biology does not offer a Master’s degree. ALL materials, including letters, are due (8:59 PST).
