49 structures-"https:" "https:" "https:" "https:" "https:" positions at Nature Careers in United States
Sort by
Refine Your Search
-
for Biology) Lab led by Dr. Christoph Gorgulla within the Center of Excellence for Data-Driven Discovery in the Structural Biology Department of St. Jude seeks a skilled and highly motivated wet lab Scientist
-
Postdoctoral Scholar in Structural Biology & Translational Medicine Are you a structural biologist looking to bridge the gap between fundamental discovery and real-world therapeutic applications
-
Lavis Lab, please visit https://www.janelia.org/lab/lavis-lab About the role: In this role, you will support the vision of Open Chemistry by designing and synthesizing fluorescent dyes and other small
-
Postdoctoral Positions for Computational Genomics, Cancer Genetics, and Translational Cancer Biology
insights through iterative, hypothesis-driven computational analysis. 2) Characterizing the landscape of structural mutations—including intragenic rearrangements (IGRs)—across cancer types and modeling
-
on understanding metabolism, cancer, and aging. More information about the lab and their work can be found by visiting https://bidmc.theopenscholar.com/kajimuralab/ About the role: As the Laboratory
-
Postdoctoral position to study Polo kinase and centrosome abnormalities in cancer and other diseases
or HIV accessory proteins, is tightly linked to the development of aneuploidy and cancer. During the past several years, we have been taking cell biological, biochemical, biophysical, and structural
-
CeMM, the Research Center for Molecular Medicine of the Austrian Academy of Sciences is committed to training the biomedical leaders of tomorrow. Our structured educational programs, hands
-
University. The position includes dedicated lab space, a competitive start-up package, and structured mentoring and promotion support. Qualifications PhD or MD/PhD in microbiology, microbial pathogenesis
-
. The candidate will lead computational analyses of these datasets, using the laboratory’s suite of existing AI/ML tools to assign structures to unidentified peaks in metabolomic datasets (e.g., https
-
interests in applied statistics, machine learning, or computational biology are encouraged to apply. For more information, please visit our website https://ds.dfci.harvard.edu/postdocs to view the list