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Field
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, Biostatistics, Computer Science, Statistical Genetics, or a related quantitative field (by the time of appointment). Strong background in statistical or machine learning methodology, optimization, or high
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data Clear scientific writing and communication; a track record of publications Experience with causal inference Bonus: experience with explainable ML, optimization/decision strategies, or work with EHR
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record of or exceptional promise for research. The fellow will work with Prof. Sam Petti on developing methods for modeling, optimizing, and interpreting biological fitness landscapes. Successful
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data Clear scientific writing and communication; a track record of publications Experience with causal inference Bonus: experience with explainable ML, optimization/decision strategies, or work with EHR
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Collaboration and Innovation Identify opportunities for process optimization and implement innovative solutions in medical communications practices. Provide mentorship to incoming fellows or interns and lead a
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outline their research plans to optimally extract cosmological information using one or multiple of these datasets. Priority will be given to candidates who can connect their science to SPHEREx, Simons
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dedicated to discovering, evaluating, optimizing, and advancing the understanding of chemical and acute non-kinetic threats, as well as medical countermeasures for safe and effective prophylaxis or treatment
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data science tools and techniques A demonstrated ability to use a statistical programming language such as R or Python for non-linear data fitting, and optimization models such as GAMS. Stipend
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in chemistry and biology, approaches for extracting relevant information from foundation models, and/or methods for adaptive experimental design such as active learning or Bayesian optimization
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at peer-reviewed venues and conferences. Example project areas Performance analysis and optimization of end-to-end scientific workflows, including those originating at DOE facilities. Operating persistent