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- Statistical learning and safe reininforcement learning - Simulation-based analysis - Explainability methods for AI/ML-based systems - Specification formalisms for learning-enabled systems We encourage
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uniformly when this is needed. Knowledge graphs are general-purpose data representations that allow for seamless exploration and interaction between semantically diverse elements, such as genomic sequences
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to formalize a biological question into a computational model. Merits: Computational genomics, medical statistics, computational biology and/or imaging analysis. Experience with NGS (10x platform, Smart-Seq
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systems is mandatory. The position requires a strong motivation for research, good verbal and written communication skills in English. Assesment criteria Additional knowledge in AI, modeling and formal
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the Wallenberg Launchpad (WALP). We are seeking a highly motivated and talented researcher with a strong background in formal verification and microarchitectural security to join our dynamic research group
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-seq, spatial transcriptomics, and highly multiplexed immunostaining. The necessary formal education to conduct animal studies according to EU legislation. Demonstrated excellent proficiency in oral and
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experiments utilizing single cell RNA-seq, spatial transcriptomics, and highly multiplexed immunostaining. The necessary formal education to conduct animal studies according to EU legislation. Demonstrated
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techniques (e.g., artificial intelligence, self-adaptation, analytics, formal methods). The EReS Research Lab integrates expertise from different research areas, such as Software Engineering and Sustainable
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in neuroscience, traumatology or equivalent. Formal education and experience of planning and conducting animal experiments. Theoretical and practical knowledge in physiological, morphological, cell and
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have demonstrated A PhD in neuroscience, traumatology or equivalent. Formal education and experience of planning and conducting animal experiments. Theoretical and practical knowledge in physiological