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methods like umbrella sampling, force integration, free energy perturbation, or lambda integration to compute the conformational behavior of individual structures and the thermodynamic stability of assembly
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Assessment Models (IAMs) such as GCAM or PAGE. The candidate must have a PhD degree in a related field, be fluent in computer programming, preferably python, and will ideally have experience in working with
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of Civil and Environmental Engineering / Chaney Lab: Perform the core of the proposed research activities including processing the remotely sensed LST to compute the spatial statistics, run the HydroBlocks
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, evolutionary biology, computer science, physics, applied mathematics, or engineering. Our research integrates mathematical modeling, machine learning, and quantitative experiments to understand and control
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proficiencywith JavaScriptand experience with B ayesian statistics are preferred.Experience in survey designis also help ful.Previous legal experience is not necessary, but an interest in law a ndlegal decision
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variable analyses including developing novel methodological approaches in collaboration with faculty statisticians · Creating table and figure output for publication · Assisting with manuscript development
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Stimulation We seek a highly-motivated individual to conduct research on computational modeling of cortical neuron activation by transcranial electric and magnetic stimulation (TES and TMS). We have an NIH
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) This postdoctoral fellow will focus on evolving and characterizing next-generation therapeutic proteins using the lab’s high-throughput phage-assisted continuous evolution (PACE) platform. Their work will contribute
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appointment is generall y preparatory for a full time academic orresearch career.The appointment is not part of a clinical training program, unlessresearch training und er the supervision of a senior mentor is
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responsibilities. The appointment is generally preparatory for a full-time academic or research career. The appointment is not part of a clinical training program unless research training under the supervision of a