207 data-"https:"-"https:"-"https:"-"https:"-"The-University-of-Tokyo" positions in Sweden
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energy models (UBEM). The work also involves using several large language models (LLM) to manage workflows, process data, develop user and building archetypes, conduct simulations, and analyze results and
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includes both scientific and technical staff with expertise in experimental neuroscience, behavioral studies, and data analysis. The position is linked to a research project investigating how humans acquire
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Troubleshoot experimental procedures and improve robustness and reproducibility Document experiments and manage data in a structured and reproducible manner Collaborate with experimental and computational team
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-how in molecular biosciences. NBIS is also the Swedish node in the European infrastructure ELIXIR for biological information. We are now strengthening our capacity in our NBIS support unit for cell and
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recruiting an outstanding and ambitious postdoctoral researcher in computational biology to advance the integration and modeling of large-scale microscopy data using modern machine learning approaches
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several cancer research groups represented, including joint seminars and other collaborative activities. The group uses various data sources and modern techniques to improve predictive modelling, including
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information about us, please visit: www.dbb.su.se . Main responsibilities We are looking for a highly motivated staff scientist to join the In Situ Sequencing (ISS). While formally affiliated with DBB
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are united in our efforts to understand, explain and improve our world and the human condition. Description of the workplace The position will be placed at the Division of Computer Vision and Machine Learning
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Doctoral student in Historical Osteology within the ERC-Synergy grant project "FORAGER" (PA2026/771)
scale and leveraging the rich legacy data already available, these issues will be addressed systematically and synergistically across four temperate regions of the Northern Hemisphere. The team will
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pathogenesis. To address this, our project utilizes novel semi-permeable capsule technology , molecular barcoding, and high-dimensional data analytics to interrogate prokaryotic cells at the single-cell level