Sort by
Refine Your Search
-
Listed
-
Employer
- AbbVie
- Northeastern University
- Zintellect
- Harvard University
- Colorado State University
- Genentech
- Nature Careers
- University of Michigan
- City of Hope
- University of Texas at Austin
- Auburn University
- Carnegie Mellon University
- Dana-Farber Cancer Institute
- Indiana University
- Marquette University
- University of California
- University of Idaho
- University of Kansas Medical Center
- University of Maryland, Baltimore
- University of North Carolina at Chapel Hill
- University of South Carolina
- University of Texas Rio Grande Valley
- GEORGETOWN UNIVERSITY
- Georgetown University
- Johns Hopkins University
- Lawrence Berkeley National Laboratory
- Massachusetts Institute of Technology
- Oklahoma State University
- Rutgers University
- SUNY
- SUNY University at Buffalo
- Saint Louis University
- San Diego State University
- The University of Iowa
- Tufts University
- University of California Los Angeles
- University of San Francisco
- 27 more »
- « less
-
Field
-
Details Title Postdoctoral Fellow in Riemannian Optimization School Harvard John A. Paulson School of Engineering and Applied Sciences Department/Area Position Description A postdoctoral position is
-
Details Title Postdoctoral Fellow in Riemannian Optimization School Harvard John A. Paulson School of Engineering and Applied Sciences Department/Area Position Description A postdoctoral position is
-
, spatial data, and perturbation screens with high content molecular and imaging data to understand cellular and multi cellular combinatorial programs in cells and tissues in health and disease. You will join
-
in the Fontana lab at Harvard Medical School in Boston Massachusetts. The work of the Fontana lab is focused on developing and applying software for modeling combinatorial systems of molecular
-
modular forms, particularly work with Klein forms and congruences satisfied by Fourier coefficients. Knowledge of special functions and q-series. Ability to deduce combinatorial information from
-
perturbation screens with high content molecular and imaging data to understand cellular and multi cellular combinatorial programs in cells and tissues in health and disease. You will join a highly collaborative
-
record of or exceptional promise for research. The fellow will work with Prof. Sam Petti on developing methods for modeling, optimizing, and interpreting biological fitness landscapes. Successful
-
characterization, and functional properties of milk proteins and peptides. Our primary research goal is to understand their impact on human health. Our current projects involve developing and optimizing methods
-
OpenFOAM. Validate the developed code and perform code optimization and parallelization. Mentor graduate and undergraduate students in their research Assist the lab director in grant proposals. Write journal
-
expected to execute across all aspects of medicinal chemistry. The candidate will be responsible for designing, synthesizing, and optimizing molecules targeting GPCRs (cannabinoid receptors; allosteric and