Mentor Areas
My lab applies a theoretical and practical understanding of population biology and statistics to contemporary problems in human genetics. My goal with this approach is to uncover how differences in DNA sequences which segregate as genetic variation across human populations contributes to the diverse set of traits that have evolved over recent human history and to the range of diseases we find today. A broad theme characterizing my lab's work through studies of complex disease and natural selection is one at forefront of human genetics, developing novel technologies, statistical methodology, bioinformatics tools, and experimental pipelines that have delivered robust analysis and biological inference, and translation in medicine. A central objective of my lab is to take vast quantities of human data available to make inference about the genetic loci and biological pathways that underlying susceptibility cardiometabolic traits, including type 2 diabetes, fatty liver, or heart disease, using statistical and informatics approaches. These insights will then be used to identify and validate new targets for therapeutics.
Description:
Specific projects can be developed with students depend on the skills, creativity, and interests of the prospective student. Please refer to research interests (lab website) or publications for examples of the types of projects the lab pursues.
Areas of active interest and example areas include:
(i) Developing and applying population genetic methods to infer natural selection still acting in human populations,
(ii) Computational approaches (i.e., statistical models or machine learning) to identify causal variants, genes, mechanisms underlying cardiometabolic traits,
(iii) Application of causal inference methods using human genetics data (i.e., Mendelian Randomization) to discover risk factors that are tractable targets for therapeutic interventions,
(iv) Integration of human genetics data with existing knowledge of small molecule therapeutics to identify new targets or indications.
Preferred Qualifications
Successful students will have a working knowledge of in one or more of the following areas: genetics, probability theory, and/or computer programming. A commitment to dedicate at least 5 hours a week to research in the lab (with allowances for exam and coursework of course as necessary). This is essential for forward progress on selected projects. Preference will be given to juniors and seniors.
Development of key technical skills (like computer programming or statistical analysis in R, etc.) or scientific knowledge (e.g., quantitative genetics or human genomics of disease) are typically integrated into to the training mission and advanced of selected research projects. Tools to ensure reproducible research will also be utilized and developed if unfamiliar (i.e., Rmarkdown, github, etc.)
Project Website
Learn more about the researcher and/or the project here. Voight Lab
Details:
Preferred Student Year
Junior, Senior
Academic Term
Fall, Spring, Summer
I prefer to have students start during the above term(s).Volunteer
Yes
Yes indicates that faculty are open to volunteers.Paid
No
Yes indicates that faculty are open to paying students they engage in their research, regardless of their work-study eligibility.Work Study
No
Yes indicates that faculty are open to hiring work-study-eligible students.