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project to integrate datasets from multiple study regions, advancing understanding of linkages between terrestrial and marine ecosystems. To thrive in this role, candidates should demonstrate expertise in
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candidates with a proven track record in developing open-source machine learning, deep learning, or cheminformatics tools (Preferred written in Python). Job Duties Plans, directs and conducts research
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The University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | 26 days ago
biophysics/chemistry. Programming skills (e.g., bash scripting, python, Fortran, C++ and CUDA), expertise in computational modeling (such as Molecular Dynamics, virtual screening, free energy calculations and
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, engineering, computational science, a physical science (materials science, chemistry, physics etc.), or related field. Hands-on experience with AI frameworks and employing large language models. Strong Python
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experience in Python and/or C++ Strong mathematical and analytical skills Has experience working collaboratively within a multidisciplinary team. Excellent oral and written communication skills as demonstrated
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Python programming skills are required, and prior experience with developing open-source software or databases will be considered a plus. Candidates should apply at: https://puwebp.princeton.edu/AcadHire
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algorithms (Python, Matlab, or equivalent). Experience with deep neural networks, particularly for the analysis of spectral or imaging data, will be highly appreciated. Knowledge of light propagation in
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(e.g., Bioconductor, Galaxy, KEGG, Reactome, STRING). Proficiency in Python, R, and Unix/Linux-based environments for high-performance data analysis. Knowledge of biological network inference, causal
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of AI and Data Science : Machine and deep learning, NLP, BDI (Belief-desire-intention) systems, and Large Language Models (LLMs). Expertise in design and very good programming skills (Python, Pytorch
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elements in nonlinear analysis software (preferred Atena); • Documented experience in other software for nonlinear analysis of structures; the ability to use a programming environment (e.g., Python) will