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Field
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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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calibration and artefact mitigation. · Develop and maintain reconstruction and data-processing pipelines using Python programming tools. · Implement quantitative 3D analysis workflows such as
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models, transformers, representation learning, contrastive methods). Solid experience with Python and Pytorch and good command of software development tools such as GIT. A good track record of authoring
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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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(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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have a Ph.D. in economics, public policy, education, or a related field by the start date, strong quantitative and econometric skills, experience coding (in Stata, Python, R, and/or SAS), and an interest
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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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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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. Basic proficiency in using Python and/or command line interface (CLI). Basic understanding of raytracing and optical design. Experience with SharePoint, SolidWorks PDM vault, GitHub. Required Documents