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at the University of Basel, Switzerland (https://duw.unibas.ch/en/ecoevo/ ), is looking for a PhD student in the field of Conservation Genetics. New computational and analytical tools in population genetics allow
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Your position New computational and analytical tools in population genetics allow to estimate both contemporary and past effective population sizes. With these in hands, the project aims to verify
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of novel physics-guided AI algorithms for drug design, integrating physics-based modeling with state-of-the-art deep learning methods. The project will focus on creating a next-generation docking framework
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) Experience in deep learning algorithms is a plus Ability to work in a highly international team and interdisciplinary project applicants are expected to have excellent language skills in English Opportunity
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the theoretical and algorithmic foundations of AI. A strong commitment to excellence in undergraduate and graduate teaching and mentorship is essential. Preference will be given to candidates who show promise in
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position (technician) will focus on performing Raman/FTIR on retrieved samples. The PhD position will focus on developing a deep-learning algorithm for analyzing the acquired experimental data.
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position (technician, this position) will focus on performing Raman/FTIR on retrieved samples. The PhD position will focus on developing a deep-learning algorithm for analyzing the acquired experimental data.
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. The PhD position will focus on developing a deep-learning algorithm for analyzing the acquired experimental data. The PhD position will focus on development a comprehensive and AI-driven platform
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has been created in theoretical quantum computing. We are particularly interested in candidates working on quantum error correction, algorithms, simulation and qubit architectures. We are also
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interdisciplinary work, for example in medicine or life sciences, who address key issues in AI such as reproducibility, safety, trustworthiness and robustness, and who engage with the theoretical and algorithmic