61 parallel-programming positions at Utrecht University in Ireland-University-Ranking-2024
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and statistical methods, including applied econometrics and panel data analysis, proficiency in a statistical programming language such as R (preferably), Python, or Stata. Prior exposure to firm-level
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(max. 10% of your time). Your qualities We are looking for an enthusiastic candidate, who has (almost) finished a Master programme in Sociology, Interdisciplinary Social Science, or a related field; has
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) Country Netherlands Type of Contract Permanent Job Status Not Applicable Hours Per Week 40.0 Is the job funded through the EU Research Framework Programme? Not funded by a EU programme Is the Job related to
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architectures; • strong programming skills in Python and experience with a deep-learning framework such as PyTorch, including training and evaluating models on GPU/HPC infrastructure; • experience working with
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; experience with foundational AI model development/fine-tuning and machine learning and/or deep learning; strong programming skills (e.g., Python, JavaScript, PostgreSQL) with clear expertise in front-end and
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of groundwater-model concepts and parameters, calibration, sensitivity analysis, scenario analysis and uncertainty assessment. Programming and data-analysis skills in a reproducible scientific workflow
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personalised training programme will be set up reflecting your training needs and career objectives. About 20% of your time will be dedicated to this training component, which includes following courses and/or
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training programme will be set up reflecting your training needs and career objectives. About 20% of your time will be dedicated to this training component, which includes following courses and/or workshops
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for a motivated candidate with strong technical and programming skills and relevant project experience to join this interdisciplinary research team at the forefront of GeoAI and question answering
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role in an inter- and transdisciplinary research community and training programme, who have: a MA/MSc degree in economic history, development or a related discipline; interest in, and ideally some