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researchers. The group conducts large-scale registry-based research covering all aspects of drug utilization, effectiveness, and safety, using Danish nationwide health registries as well as international data
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process engineering and covers a large part of the TRL ladder. This includes basic research as well as activities within demonstration and pilot-scale testing of renewable energy technologies. Co-operation
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Postdoc in pharmacoepidemiology: Long-term safety and benefits of ADHD medication in children and...
. Core research tasks include planning, conducting and publishing epidemiological studies using large-scale observational data, primarily register-based, with a focus on effects of ADHD medication in both
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. Weinstein (DTU Chemistry) to develop novel molecular ML methods and use them to control, steer, and learn from large scale wetlab experiments. You will deploy these methods in collaboration with Prof. Katrine
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potential possibility for extension. Job description You will be part of a large interdisciplinary consortium project studying the effect of pesticides and environmental toxicants on the development
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. Applicants seeking further information are invited to contact Associate Professor Florin Musat (florin.musat@bio.au.dk) . Who we are The successful candidate will be employed by the Department of Biology at
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-ribosylation or PARP biology Experience with high-resolution LC-MS systems, PTM enrichment strategies, or large-scale proteomics experiments will be considered an advantage. The ideal candidate is
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econometric methods for analysing large datasets. Are proficient in coding and data management using tools such as Stata, R, or Python. Have a strong interest in the research area and have a strong independent
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extensive use of surface science methods and also includes the most advanced methods of microscopy through its collaboration with VISION. Visiting large scale facilities such as synchrotrons for EXAFS and
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at the Department of Electrical and Computer Engineering, Aarhus University, where we are advancing communication-efficient and distributed foundation model inference across the computing continuum