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. We are now looking for: Three (3) Doctoral Researchers (PhD students) in Machine-Learning-Driven Atomistic Simulations The Data-driven Atomistic Simulation (DAS) group, led by Prof. Miguel Caro
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2025, or as soon as possible thereafter. The project explores two parallel technological routes for converting captured carbon dioxide into microbial biomass: One fully biological, and the other a hybrid
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. Among the methods used are high-throughput CRISPR screening, protein deep mutational scanning, massively parallel reporter assays, and genetic manipulation of cell lines and mice. The successful candidate
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Postdoctoral Appointee - Uncertainty Quantification and Modeling of Large-Scale Dynamics in Networks
Requirements Required skills, abilities, and knowledge: Recent or soon-to-be completed PhD (within the last 0-5 years) by the start of the appointment in computer science, electrical engineering, applied
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. In parallel with your experimental work, you would develop theoretical models in collaboration with our international collaborators. You would also develop advanced image analysis schemes to analyse
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platform enables us to test hundreds of different conditions in parallel and assess their impacts on human immune responses, such as antibody production. We routinely work with industry partners to exploit
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2019 https://doi.org/10.1038/s41596-018-0110-x and Lara et al., arXiv:2503.21396 https://doi.org/10.48550/arXiv.2503.21396 )). In parallel with your experimental work, you would develop theoretical
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. Qualifications: • A PhD in applied mathematics, statistics, electrical engineering or computational sciences completed within the past 5 years (or soon to be completed) • Experience in numerical analysis and
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Education At the time of hiring, a PhD in Solid state Physics, Theoretical Chemistry, Computational Materials Science, or related fields. Required Experience Strong foundation in Quantum Mechanics and
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for multiple-CPU and/or GPU platforms via parallelization schemes. Validating these codes via canonical and real-world examples. Job Requirements: PhD in Electrical and Electronic Engineering, Applied