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physics, applied mathematics, machine learning, bioinformatics, biophysics, spectroscopy, image processing, ecological modeling, molecular biology, plant physiology, marine biology or an interest in gaining
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motion planning - Predictive collaboration with heterogeneous teaming - Multi-agent navigation in constrained environments - Data-driven and learning based control - Meta-learning for emergent behavior in
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sequences, with applications ranging from biogeographical mapping to paleogenetic reconstructions. The candidate will work jointly with Dr. Eran Elhaik to design machine-learning models that unlock
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simulations to experiments in subatomic physics. The Plasma Theory group within the Division conducts research on acceleration and radiation generation in magnetic fusion, laser-produced and astrophysical
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modeling, machine learning, and experimental studies, while offering the opportunity to contribute to open-source libraries and collaborate directly with an innovative startup partner. You will be
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scientific research publications. Your profile Required qualifications PhD in Chemistry, Chemical Engineering, Physics, Catalysis, Materials Science or equivalent (awarded no more than three years prior
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reporting current research results in both written and oral form as well as authoring scientific research publications. Your profile Required qualifications PhD in Chemistry, Chemical Engineering, Physics
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research. The methods of our investigations are also diverse and complementary, and range from theory and computer simulations to experiments in subatomic physics. The Plasma Theory group within the Division
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curious and motivated postdoc with a PhD in biomedical engineering, physics, materials science, organic chemistry—or similar—and a drive to explore new frontiers in science. 👉 Learn more and apply here
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combine large-scale data, computational methods, and clearly articulated social-science theories to improve our understanding of society. Recent advances in machine learning, natural language processing