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data-driven, computational approaches. Successful candidates will be willing and able to work across a breadth of disciplines - from genomics to computer science, sociology to psychology, engineering to
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advanced microscopy techniques and related methods. Candidates who are nearing completion of their Ph.D. (i.e. with a confirmed defense date) or hold a Ph.D. in chemical engineering, chemistry, materials
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interested in computational materials design and discovery. The successful candidate will develop new, openly accessible datasets and machine learning models for modeling redox-active solid-state materials
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have or be expected to have a PhD with appropriate research experience in computational biology, chemistry, biochemistry, computer science, biological or chemical engineering, forensic science, or a
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Department of Chemical and Biological Engineering at Princeton University. The position is in the broad area of renewable energy systems synthesis, analysis, and optimization. The goal of the project is to
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the Andlinger Center for Energy and the Environment and the Department of Chemical and Biological Engineering at Princeton University. The position is in the broad area of renewable energy systems synthesis
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interested in computational materials design and discovery. The successful candidate will develop new, openly accessible datasets and machine learning models for modeling redox-active solid-state materials
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background in chemical and biological engineering, bio-engineering, molecular biology, microbiology, biochemistry, biophysics, computational modeling or related fields. Experience in metabolic engineering
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advanced microscopy techniques and related methods. Candidates who are nearing completion of their Ph.D. (i.e. with a confirmed defense date) or hold a Ph.D. in chemical engineering, chemistry, materials
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: 275950536 Position: Postdoctoral Research Associate in Microfluidics, Nanofabrication, and Nanophotonics Description: The Department of Electrical and Computer Engineering has opening for postdoctoral