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/biophysics, ion channels, or electrophysiology Candidates who have been highly productive with motivation and passion for science and a wide range of research experiences are encouraged to apply. BACKGROUND
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available codes and existing high performance computing (HPC) infrastructure Identify key physics of the systems through simulations to drive actionable design recommendations Identify gaps between existing
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, biochemistry, neuroscience, or related fields. Experience in one of the following areas is preferred: mitochondrial physiology, protein biochemistry/biophysics, structural biology, ion channel electrophysiology
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Scientific Machine Learning. The successful candidate will develop and deploy state-of-the-art SciML algorithms in high-performance computational physics codes. We accept applications from all candidates with
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astrophysics. The successful candidate will lead the implementation of new features in the AthenaK code, in collaboration with Dr. David Radice (Penn State) and Dr. Jim Stone (IAS), and they will participate