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(relative to degree timing) *Collaborative spirit in interacting with postdoctoral and PhD researchers on the team *Interest in developing and applying Large Language Models (LLM) and spatial Machine Learning
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] Subject Areas: Computational Biology / Data Analytics Analytical Chemistry / Current Advances in Chemistry & Biochemistry Machine Learning / Machine Learning Computational Science and Engineering
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psychoactive substances, in seized drug products or clinical samples. The candidate will have the opportunity to work directly with experimentalists to validate predictions made by their machine-learning models
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, multiscale modeling, molecular simulation code/software (e.g., LAMMPS, GROMACS), machine learning. Prior experience with applying simulations to biomolecular systems is a plus but not required. Applicants
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acids, ligands), coarse-grain and polymer model development, multiscale modeling, molecular simulation code/software (e.g., LAMMPS, GROMACS), machine learning. Prior experience with applying simulations
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d) excellent written, oral communication skills e) strong data analysis skills. Ideal applicants will also have experience with some combination of: a) Machine learning e) code optimization and
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theoretical computer science and theoretical machine learning. The Term of appointment is based on rank. Positions at the postdoctoral rank are for one year with the possibility of renewal pending satisfactory
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; advanced causal inference and statistics; computer vision and novel applications of machine learning. Advanced knowledge of R or Python is required. Intermediate knowledge in C/C++ and/or at least one SQL
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d) excellent written, oral communication skills e) strong data analysis skills. Ideal applicants will also have experience with some combination of: a) Machine learning e) code optimization and
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and machine learning with Prof. Jason M. Klusowski (https://klusowski.princeton.edu). The position is for one year with the possibility of reappointment based on satisfactory performance and