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Field
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collaboration with industry partners and SMEs. You have a track record of scientific publications in relevant venues. You are proficient in Python and relevant machine learning frameworks such as PyTorch
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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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data analysis skills, including experience with R, Python, MATLAB • Excellent written and verbal communication skills • Strong organizational and interpersonal skills and ability to work collaboratively
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engineering pipelines. Implement models in Python using frameworks such as PyTorch, TensorFlow. Perform statistical analyses and model benchmarking against existing methods. Collaborate with wet-lab scientists
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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
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acquisition, instrument control, and data analysis in Python or similar languages Knowledge of quantum optics measurements such as photon correlation functions or photon-number-resolved detection Familiarity
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advanced analytical skills including statistical programming in Python, Stata, R, and/or SAS • Excellent communication and presentation skills • An ability to work both independently and in teams Benefits
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the data from HEP experiments is strongly required Programming expertise in Python and either PyTorch or TensorFlow is required Experience using High-Performance Computers (HPCs) is preferred Ability