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PhD Position in Theoretical Machine Learning – Understanding Transformers through Information Theory
Join us for a fully funded PhD position in theoretical machine learning to uncover how and why transformers work. Explore their inner mechanisms using information theory. As part of this project
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. The research program “Save the Ash”, managed by Skogforsk and SLU, aims to develop a more resistant population of European ash for the future. The PhD project will investigate the recent rapid decline in
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and computational methods within quantum mechanics and statistical physics with the aim to design alloys for rare-earth-free high-performance permanent magnets. You will use computational techniques
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First Stage Researcher (R1) Country Sweden Application Deadline 25 Mar 2025 - 22:59 (UTC) Type of Contract Not Applicable Job Status Full-time Is the job funded through the EU Research Framework Programme
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models, also through neuroadaptations in the opioid and dopamine systems. However, little is known about the molecular mechanisms underlying the effects of the social environment on alcohol use, or about
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) program. Data-driven life science (DDLS) uses data, computational methods and artificial intelligence to study biological systems and processes at all levels, from molecular structures and cellular
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thesis project will focus on drug resistance mechanisms in microbiome species. The position is for four years of doctoral studies, including participation in research and postgraduate courses. The last day
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flow phenomena. The goal is to integrate theoretical and experimental fluid dynamics with modern computational tools to analyze and predict multiphase flow behavior. The project also involves applying
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supported by the SciLifeLab and Wallenberg National Program. The research group at the Department of Medical Biochemistry and Microbiology where the candidate will be joining is focusing on mechanisms and
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and experiences. We regard gender equality and diversity as a strength and an asset. The SciLifeLab and Wallenberg National Program for Data-Driven Life Science (DDLS) is a 12-yr initiative funded with