884 machine-learning "https:" "https:" "https:" "https:" "https:" "The University of Edinburgh" positions in Sweden
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. Where to apply Website https://lu.varbi.com/en/what:job/jobID:906273/type:job/where:39/apply:1 Requirements Research FieldMedical sciencesEducation LevelPhD or equivalent Research FieldMedical
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600 studenter. We are looking for you who have great ambitions in research as well as in teaching and learning, for a postdoctoral position within our research subject, Product Innovation. The research
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knowledge. The required training for teachers in higher education may be completed during the first two years of employment if there are exceptional grounds. documented ability to teach in Swedish or English
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, such as pulse design or numerical optimization Background in data-driven or machine-learning approaches relevant to optimal control (e.g., model learning, reinforcement learning) What you will do Take
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. Previous experience with machine learning applications in molecular modelling, including experience with at least three of the following Python libraries: TensorFlow, PyTorch, JAX, RDKit. Previous
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an innovative spirit, in close collaboration with wider society. Chalmers was founded in 1829 and has the same motto today as it did then: Avancez – forward. Where to apply Website https://academicpositions.com
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terms The Doctoral student positions are fully funded from start. The position is a fixed-term appointment of four years, with the possibility to teach up to 20%, which extends the position up to five
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, globalisation and econometrics. The position is specifically at the AI-Econ Lab at Örebro University (https://www.ai-econlab.com ) – an international and interdisciplinary research lab that focuses
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computational methodologies, ranging from atomistic and electronic-structure–based materials modeling and characterization, via machine-learning and high-throughput methods, to ab initio calculation
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and CH4) from headwaters, and use of machine learning and process-based model for large scale assessments and projections of the land-water carbon cycle to variation in climate conditions. The detailed