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Field
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scalability of simulation workflows via: Parallelization and performance engineering GPU/accelerator optimization Algorithmic innovation Experience applying machine learning or AI to molecular simulation
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freely behaving rodent pups. A parallel research line investigates the circuit-level basis of spatial memory in the entorhinal–hippocampal system in adult animals. The group uses in vivo multi-site
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introduced by our group while developing new ones, and we couple this work with innovative strategies to define the molecular basis for their modes of action in bacterial cells. In parallel, we investigate how
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dynamics simulations, statistical mechanics, and electronic structure theory. Proficiency in scientific programming is essential, with experience in Python, Fortran, and parallel computing frameworks (e.g
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associated with biological membranes, including large peripheral membrane complexes and integral membrane transporters. In parallel with mechanistic structural work, we develop targeted chemical probes
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. Integrate the feed chemistry data being developed in a parallel project. Travel to India to help implement the updated model. This would be as needed and no more than two times per year. Conduct a comparative
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their own research program in collaboration with, and in parallel to, Prof. Zanazzi. Penn State hosts a vibrant community of scientists working on many aspects of exoplanetary astrophysics, including
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parallel programming. ● Experience with writing scientific articles. ● Experience with writing scientific machine learning. Overtime Status Exempt: Not eligible for overtime Appointment Type Restricted
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editing, PCR, Sanger sequencing Track-record of first-author publications in reputable peer-reviewed journals Demonstrated self-initiative and motivation, ability to collaborate, organize parallel
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Lab researches on a variety of computer systems topics including HPC resilience, data center power management, large-scale job scheduling and performance tuning, parallel storage systems and scientific