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computational materials science techniques (DFT, MD, machine learning force fields) with data-driven approaches. Design and implement high-throughput experimental workflows for thermal conductivity and phonon
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dynamics in the machine-learning predictions, we aim to understand drivers of predictability: are there “windows of opportunity” of high predictive skill which may benefit farmers? Please note that this post
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for publications. Job Requirements: PhD in organic chemistry At least 5 years of experience in synthetic organic chemistry and/or asymmetric catalysis as PhD/post-doc in advanced institutions. Solid analytical
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Details Title Postdoctoral Fellow in Machine Learning and Design of Biological Systems School Faculty of Arts and Sciences Department/Area Science Division Position Description A postdoctoral
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settings, inpatient settings, and elective rotations in specialized ambulatory settings providing health care services within defined scope of practice in collaboration with a licensed physician and in
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contribute to the collaborative TQT research community. Principal Investigator: Na Young Kim Project Name: Solid-state analog Optimization Solver and Quantum Machine Learning (Theory) Research Area
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organoids will be plus. Dry lab: Highly motivated candidates with a PhD/MD degree in bioinformatics, genome science, systems biology, biomedical informatics, computational biology, machine learning, data
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machine learning methods to the analysis of large-scale astronomical datasets, with a particular emphasis on time-domain astronomy. Research directions will be flexible and shaped according to mutual
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exciting project that will develop new approaches to handle missing data in statistical analyses based on machine learning methods. The Research Fellow will be based in the Department of Medical Statistics
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Details Posted: Unknown Location: Salary: Summary: Summary here. Details Posted: 19-Aug-25 Location: Boston, Massachusetts Type: Full-time Categories: Academic/Faculty Physical Sciences Internal