74 scholarship-phd-agent-based-modelling Postdoctoral positions at Technical University of Denmark
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capture. The research is based on strong competences on electrochemistry, atomic scale and multi-physics modelling, autonomous materials discovery, materials processing, and structural analyses. We also
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, clinics and regulation) Publish research findings in peer-reviewed journals and present at international conferences Qualifications: As a formal qualification, you must hold a PhD degree (or equivalent) in
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. Desirable criteria Experience working with generative models or large language models Experience with GPU-based model training or cloud computing Knowledge of synthetic biology or regulatory sequence design
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FTIR, EPR, XPS, Raman) and DFT-based electronic structure analysis (in collaboration) to elucidate structure–activity relationships. Analyze reaction products, selectivity, and mass balance for both
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models Tough bio-inks for surgical procedures We are looking for candidates with a high degree of independence and a strong drive for scientific excellence. These positions provide excellent opportunities
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consortium. As a formal qualification, you must hold a PhD degree (or equivalent). Other qualifications and competences include: Experience with mathematical modelling Experience with toxicology Experience
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writing scientific papers. The developed models will be tested on data from energy investment models, as well as transport infrastructure problems. We will be an academic team of three PhD students and four
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based on strong competences on electrochemistry, atomic scale and multi-physics modelling, autonomous materials discovery, materials processing, and structural analyses. We also focus on educating
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communication skills are required for this position. We are seeking a bright and empathic person with a PhD in materials science, materials science in soft and biomaterials, MEMS processes, advanced lithography
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/or high-temperature heat pumps based on power cycles. Design thermal and/or thermochemical energy storage systems. Implementing and validating advanced thermodynamic models for performance prediction