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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
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of possible methodological components include self-supervised temporal representation learning for large volumes of unlabeled AE/electrochemical time-series data, switching state-space models that describe
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12 Dec 2025 Job Information Organisation/Company Lunds universitet Department Lund University Research Field Biological sciences » Other Chemistry » Other Agricultural sciences » Other Researcher
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methods to rigorously assess the safety and effectiveness of medications in real-world patient populations. Defining individualized treatment strategies: Leveraging traditional and causal machine learning
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-renal diseases. Our research spans large-scale register and laboratory data, causal and predictive modeling, and computational image analysis of kidney biopsies. About the Research Group: Led by Professor
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laboratory-based research with large-scale trials in real production environments to develop globally applicable solutions that reduce food waste and enhance shelf life. Subject description Fruit and
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learning and its application 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
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description and working tasks The project will develop privacy-aware machine learning (ML) models. We focus on data-driven models for complex and temporal data, including those built from synthetic sources
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, obtained within the last three years prior to the application deadline Strong background in machine learning, statistical modeling, and big-data analytics. Experience with infrastructure or transportation
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environment for all employees through mutual respect and tolerance. Description of the project The postdoc will leverage existing high-throughput data from large scale cohorts and large family cohorts