27 data-"https:"-"https:"-"https:"-"https:"-"https:"-"Stanford-University" positions at University of Basel
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Your position • Maintain and enhance pipelines for spike sorting, calcium imaging signal extraction, neuron tracking across recordings, and automated behavioral analysis. • Develop efficient data
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Postdoctoral Researcher in Marketing (AI & Synthetic Data) 80-100% Join the Marketing Group at the University of Basel to advance research on synthetic data. In an Innosuisse project with Boomerang
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12 Dec 2025 Job Information Organisation/Company University of Basel Research Field Biological sciences » Biology Computer science » Other Mathematics » Statistics Neurosciences » Neurology
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personal references (letter or contact details) For further information, contact: Dr. Andrea Bublitz, Marketing, University of Basel, andrea.bublitz@unibas.ch . Where to apply Website https
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will be responsible for a range of research tasks, including literature search, data curation, coding for systematic literature reviews, data analysis, and miscellaneous administrative activities (e.g
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maintain infrastructure and lab equipment (e.g. microtomes, automated stainers, and tissue processors). Track and manage samples and data with precision. Develop new protocols and methods. Implement quality
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vision and its associated diseases, as well as to develop new therapies for vision loss. For more information, please visit iob.ch ! About the project For a project in the Human Retinal & Central Visual
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multimodal data analysis, with an initial focus on neuroscience. To build this interdisciplinary platform, we invite applications for three PhD-level Research Specialists: Microscopy and Spatial
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Health (AICH) group develops AI/ML methods, digital tools, and secure data pipelines to advance pediatric healthcare. We work at the intersection of clinical medicine, machine learning, and data-intensive
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-focused , contributing primarily to one of the following projects: Project A – Synthetic Data for Theory-Driven Behavioral Research This project investigates how large language models (LLMs) produce