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Field
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conducting research "in the wild" (e.g., field deployments or data collection in real-world environments) Familiarity with current AI technologies (e.g., machine learning, large language models) and an
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electrochemistry Demonstrated ability to work independently Excellent command of the English language, good communication, and team working skills If not already proficient, be willing and able to learn X-ray
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computational costs by orders of magnitude and enabling breakthroughs in drug design and materials science. The position bridges machine learning and molecular science, with opportunities for collaboration
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forest growth, survival and biodiversity for the future use and conservation of forests. More information: https://www.slu.se/en/wiforce . The work aims to generate new knowledge and contribute
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addition to conventional software, the scope includes engineering of AI enabled systems (primarily ML and LLM), and thus MLOps (Machine Learning Operations), datacentric AI, and legal and ethical aspects of AI
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the Arctic, experimental tests of climate driven changes in carbon export from land and turnover and release of greenhouse gases (CO2 and CH4 ) from headwaters, and use of machine learning and process-based
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within applied mathematics, materials science, physics and building science. Mathematical statistics is an important part of these four areas of research. Relevant applications include machine learning
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includes, for example, the areas of labour markets, wellbeing and welfare, macro-financing, globalisation and econometrics. The position is specifically at the AI-Econ Lab at Örebro University (https
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university and public authority. Learn more about our benefits and what it's like to work and grow at KTH Type of employment: Temporary position Contract type: Full time First day of employment: 2026-08-17
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university and public authority. Learn more about our benefits and what it's like to work and grow at KTH Type of employment: Temporary position Contract type: Full time First day of employment: 2026-08-17