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Massachusetts Institute of Technology | Cambridge, Massachusetts | United States | about 18 hours ago
; strong physical, mathematical, and computational background; experience with programming in at least one general-purpose language (preferably Julia) and parallel computing; demonstrated effective written
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of atmospheric aerosols and parallel computing/software development is strongly desired. The term of appointment is based on rank. Positions at the postdoctoral rank are for one year with the possibility
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and risk assessment modeling. • Prior experience with CCUS research projects. • Familiarity with high-performance computing (HPC) and parallel computing techniques. Required Knowledge, Skills, and/or
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professional responsibilities of the specialty occupation position. This requirement is common to this industry in parallel positions among similar organizations. The annual base salary range for this position
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/neuropixel probes and electrical microstimulation to study attention and decision making networks in a behaving animal model together with parallel studies in humans. The project is part of a NIMH Silvio O
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, excursions) Global geo-/paleomagnetic field modelling expertise is advantageous Strong programming skills, preferably in Fortran, Python and/or Matlab, parallel programming Experience in international
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leading peer-reviewed journals and conferences. Researching and developing parallel/scalable uncertainty visualization algorithms using HPC resources. Collaboration with domain scientists for demonstration
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platform enables us to test hundreds of different conditions in parallel and assess their impacts on human immune responses, such as antibody production. We routinely work with industry partners to exploit
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of parallel synthesis and purification methods is required. Some experience in molecular modeling and/or protein-inhibitor visualization is a plus. The incumbent must be able to synthesize, purify, crystallize
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of laminar/neuropixel probes and electrical microstimulation to study attention and decision making networks in a behaving animal model together with parallel studies in humans. The project is part of a NIMH