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CellProfiler. Competence in machine learning or statistical modelling for high-dimensional biological data. Prior experience from translational oncology or working closely with clinicians and clinical trials
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, machine learning, database systems, or data mining. Experience with different generative AI approaches such as transformer, or diffusion models. Very good programming skills in either Python, Julia, or R
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different generative AI approaches such as transformer, or diffusion models. Very good programming skills in either Python, Julia, or R. Have excellent skills in mathematics and probabilistic AI. Good written
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measurement quality issues related to respondent non-compliance in ecological momentary assessment or exploring the use of machine learning techniques to aid the estimation of item response theory (IRT) models
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, operational, and economic considerations. The research will involve: Mathematical modeling of measurement uncertainty and its impact on decision-making. Physics-based simulations of drilling dynamics under
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technical, operational, and economic considerations. The research will involve: Mathematical modeling of measurement uncertainty and its impact on decision-making. Physics-based simulations of drilling
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or exploring the use of machine learning techniques to aid the estimation of item response theory (IRT) models in small samples. The appointment is a full-time position and is made for a period of three years
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ecosystems. The Postdoc fellow will engage with developing and finetuning models from the provided by the partners data (e.g., small models, employ RAGs) and investigate the possibility to include those models
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learning, including designing, developing and evaluating systems and models to enhance learning through AI technology. The Postdoc fellow will engage with developing AI-agents, models, frameworks and
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environments, including but not limited to Generative AI and multi-agent ecosystems. The Postdoc fellow will engage with developing and finetuning models from the provided by the partners data (e.g., small