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and automated floor-plan recognition, to fill data gaps and harmonise information from disparate sources. Learn more and watch our project video here: https://sb.chalmers.se/digital-material-inventories
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disorder. This project investigates early neural markers of psychosis by integrating multimodal neuroimaging with genetic and transcriptomic data and applying machine-learning approaches to identify
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testing and collaboration with infrastructure owners or managers - Experience in supervision - Knowledge of data-driven methods, signal processing, or machine learning - Familiarity with sustainable
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The applicant must: hold a PhD in a relevant field (e.g. computer science, artificial intelligence, machine learning, computer vision, animal science, biology, veterinary medicine, or a related discipline) have
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within the Data Science & AI division (DSAI). With 30+ nationalities and strong industry/academic ties, we offer a dynamic, collaborative ecosystem. The AI and Machine Learning in the Natural Sciences
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Laszlo Bakó (molecular biology) and Torgeir R. Hvidsten (comparative genomics). The environment provides comprehensive support for large‑scale multi‑omic data generation/analysis and transformation
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-of-computing-science/ Project description and working tasks The project will develop privacy-aware machine learning (ML) models. We are interested in data driven models for complex data, including temporal data
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) Chalmers/University of Gothenburg drives cutting-edge research in machine learning and its application within the Data Science & AI division (DSAI). With 30+ nationalities and strong industry/academic ties
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17 Jan 2026 Job Information Organisation/Company Lunds universitet Department Lund University, LTH, Department of Energy Sciences Research Field Engineering Researcher Profile Recognised Researcher
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/or spatial genomics, computational biology, machine learning, bioinformatics, and systems neuroscience. Prior experience with deep learning applied to biological data is a plus. Practical experience