Sort by
Refine Your Search
-
Employer
- Stony Brook University
- Yale University
- Lehigh University
- Rutgers University
- University of Washington
- Harvard University
- Pennsylvania State University
- Princeton University
- Texas A&M University
- University of Minnesota
- University of North Carolina at Chapel Hill
- Zintellect
- Cornell University
- Fred Hutchinson Cancer Center
- Indiana University
- Montana State University
- New York University
- St Jude Children's Research Hospital
- Stowers Institute for Medical Research
- Texas A&M AgriLife
- The University of Arizona
- University of Massachusetts Chan Medical School
- University of Miami
- University of New Orleans
- University of Oregon
- University of Southern California
- Virginia Tech
- 17 more »
- « less
-
Field
-
in conducting experimental, computational, and comparative work to understand how changes in gene expression underlie insect diet specialization and sequestration. They will be expected to come to
-
affiliates reflect strengths in machine learning, biological modeling, data ethics, data sovereignty, computer science, environmental data science, climate change policy and modeling, evolutionary genetics
-
Apply now Job no:503761 Work type:Exempt Staff Full-time Location:Bethlehem Categories:Postdoc The Schultz Lab is seeking highly motivated PhD-level scientists to lead computational or hybrid wet
-
Postdoctoral Association and Yale Office for Career Strategy. Qualifications Candidates should have or be close to obtaining a PhD in either genetics/genomics, evolutionary biology, computational biology, or a
-
University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | about 2 months ago
background in microbial genomics, evolutionary biology, bioinformatics, or computational biology, with an interest in translational applications that connect bacterial evolution to clinical impact. Experience
-
: Using biogeochemical evolutionary models to simulate lifeless and inhabited worlds, and Developing disequilibrium-, redox-, and information-based metrics to understand and quantify the influence of life