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. Strong Python and machine learning skills; experience with LLM post-training, reinforcement learning or user studies is a plus. A publication record demonstrating original contributions to NLP, AI or
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, particularly LLM reasoning, semantic representation or user modeling. Strong Python and machine learning skills; experience with knowledge graphs or human–AI interaction is a plus. A publication record
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field, completed by the start date or with the defence scheduled this year. Strong applied machine learning skills and fluency in R and/or Python Experience with intensive longitudinal, sensing, or other
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programming languages and frameworks such as Python, PyTorch, or TensorFlow is an advantage Fulfillment of the formal admission requirements for doctoral studies at the University of St. Gallen
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data (e.g., Refinitiv, PitchBook, etc.) and experience with experimental or survey-based methods is a plus; experience with programming languages and statistical software (e.g., R, Stata, or Python
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) Interest or experience in multi-modal data integration and trajectory inference Proficiency in Python and/or R Interest in developmental and human biology is highly valued, but not required Strong
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• Previous knowledge about nanopore experiments, protein purification, and/or machine learning is a clear plus. • Experience in data analysis and coding (preferably Python) • A systematic
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. Hands-on experience with quantitative microscopy (live-cell imaging, high-content screening, or single-cell/single-bacterium imaging) Comfort with image analysis pipelines and scripting (Python
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Experience with femtosecond lasers and/or quantum optics is a plus Experience with scientific programming and data analysis (Python, MATLAB, or similar) is a plus Communication and team-working skills We
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, Cheminformatics, Computer Science, Physics, or a related discipline. Strong background in machine learning and deep learning. Strong programming skills, particularly in Python. Experience in at least one of