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Field
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and Python programming skills are an advantage. Passionate about science communication and cultivating collaborative relationships with industry professionals. Excellent written and spoken English. A
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, including hands-on implementation Strong understanding of machine learning models and their development Strong analytical, problem solver, and programming skills for Python and Matlab are preferred Experience
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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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, 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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using a range of specialised research techniques. Good knowledge of the R statistical programming language. Programming experience in C, C++ or Python is desirable. Excellent verbal and written
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cancer biology, molecular/cellular biology, genomics, or immunology with expertise in gene editing technology and NGS; flow cytometry and cell sorting; and bioinformatic and data integration, R/Python
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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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. 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
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Python and/or R are essential. Excellent communication skills and the ability to collaborate effectively in interdisciplinary research environments are also required. This is a full time, fixed term post