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David J. Ross (Fed)
Physicist
David Ross is the lead scientist for the Living Measurement Systems Foundry in the Cellular Engineering Group at NIST. He currently works on methods for predictive engineering of biological function. His most recent work has focused on developing measurements and standards for large-scale, AI-ready biological data and machine-learning approaches to predict protein function using large-scale data.
Postdoctoral Research Opportunities
National Research Council Research Associateship Program at NIST:
- Rolling application deadlines Feb. 1 and Aug. 1
- US citizens only
- $82,764 annual salary plus benefits
- Please contact me directly and see the following link for further details:
Positions for non-US citizens:
- Please contact Dr. Ross directly
Selected Publications (Google Scholar)
- “Interpretable modeling of genotype-phenotype landscapes with state-of-the-art predictive power”
PD Tonner, A Pressman, D Ross
Proc. Natl. Acad. Sci. U.S.A. 119 (26) e2114021119 (2022), https://doi.org/10.1073/pnas.2114021119 - “Interpretable modeling of genotype-phenotype landscapes with state-of-the-art predictive power”
S d'Oelsnitz et al.
Research Square (2021), https://doi.org/10.21203/rs.3.rs-5861295/v1 - “The genotype‐phenotype landscape of an allosteric protein”
DS Tack et al.
Molecular systems biology 17 (3), e10179 (2021); https://doi.org/10.15252/msb.202010179 - “Genetic circuit design automation”
AAK Nielsen, et al.
Science 352 (6281), aac7341 (2016); https://doi.org/10.1126/science.aac7341 - “Equilibrium free energies from non-equilibrium trajectories with relaxation fluctuation spectroscopy”
D Ross et al.
Nature Physics 14 (8), 842-847 (2018); https://doi.org/10.1038/s41567-018-0153-5 - “Microfluidic temperature gradient focusing”
D Ross, LE Locascio
Analytical chemistry 74 (11), 2556-2564 (2002); https://doi.org/10.1021/ac025528w - “Observation of short-range critical wetting”
D Ross, D Bonn, J Meunier
Nature 400 (6746), 737-739 (1999); https://doi.org/10.1038/23425