202 computer-security-"https:"-"https:"-"https:"-"https:"-"UCL" positions in Switzerland
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Neuroanatomy, and using model systems relevant to human development or disease. You will also be expected to secure competitive research funding and publish high-quality papers in your field. Alongside your
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to commercial-grade systems, we are seeking a visionary Lead Architect to drive the design and development of the V2.0 system. This role is critical for establishing technical novelty, securing a new IP portfolio
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to study and predict. In this four-year SNF-funded project, you will develop data-driven, multiscale simulation methods that combine computer simulations, machine learning, and surrogate models to explore
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. This international PhD is part of the Collaborative Doctoral Partnerships programme, training researchers at the science-policy interface. Your profile Qualification and specific competences required Master's degree
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contribute to interindividual differences in drug response and safety. We employ a translational approach that integrates preclinical in vitro and in vivo studies with clinical investigations in our
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. Profile Ph.D. in Nuclear Engineering, Physics, Chemical Engineering, or a related field. Experience with computational chemistry and simulation tools. Prior knowledge of nuclear safety, severe accident
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100%, Basel, fixed-term The Computational Biology (CoBi) group, led by Prof. Dagmar Iber, develops data-driven, mechanistic models of biological systems using advanced imaging and computational
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work closely with Professor Platt, guide the group’s computational research, contribute to ongoing projects, and pursue independent research directions aligned with the laboratory’s goals. Project
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organised individual to support multiple experimental and computational research groups. The successful candidate will contribute to both a collaborative research network and institute-wide activities
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-phonon coupling elements. With these, dedicated scattering rates can be computed and then used in quantum transport simulations. Down the line, we aim to pre-train a common GNN backbone model capable