196 cloud-computing-"https:"-"https:"-"https:"-"https:"-"https:"-"BioData" positions in Switzerland
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experimental-design principles, especially as applied to perturbation-effect estimation at both perturbation and gene levels. Bioinformatics workflow design (Snakemake/Nextflow) and HPC/cloud computing
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-facturing processes. In this internship, you will work on state-of-the-art anomaly detection methods using computer vision and time-series data, with a particular focus on multimodal data fusion for powder
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, neuroscientists, computer scientists, clinicians, and data scientists across the Singapore-ETH Centre (SEC), the National University of Singapore (NUS), and Nanyang Technological University (NTU), the PhD student
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Computer Vision and Computer Graphics techniques to digitize human avatars and garments in 3D. Within this project, your role is to advance our existing algorithms that reconstruct 3D garments from multi
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Doctoral School candidates must submit their application file to the doctoral program of their choice within the deadlines specified by the latter. Some programs publish open positions related
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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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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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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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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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-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