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) therapy on the biology of γδ T cells and how can we use this knowledge to help us predict the success of therapy and prevent the development of side-effects. Position 1 will focus on the cellular and
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Job Description Are you passionate about renewable energy and eager to apply machine learning to real-world challenges? Join our research team at DTU and work on groundbreaking advancements in
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Laboratory techniques for sample preparation Analysis of mass spectrometric datasets and statistical calculations Contribute to in vitro analyses Contribute to carrying out animal experiments Contribute
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in functional genomics methods (e.g., single-cell and bulk RNA-seq, ATAC-seq and ChIP-seq) and computational data analysis is considered highly advantageous. Selected references: Jakobsen et al., 2024
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, Biomedicine, or Computational Systems Biology. Experience with NGS data or single cell-sequencing analysis is required. Competence in adipose tissue biology, cell culture work or mouse physiology would be
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machine learning for safe and optimal control of cyber-physical systems. The projects are expected to be funded by the VILLUM INVESTIGATOR project S4OS (“Scalable analysis and synthesis of safe, secure and
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University of Munich (TUM) , focusing on cutting-edge research in digital health, wearable sensing, and embedded artificial intelligence. The Project title is ‘IoT-based Assisted Living’ and the main purpose
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the European Innovation Council (EIC), you will work in close collaboration with researchers at DTU, Cambridge University, Technical University Munich, Imperial College London and the company SolarFoods. You
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large dataset analysis, improving decision-making processes for awarding grants to firms and scientists. The PhD project could aim at the following issues: Improved Funding Decisions: How can we make
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to improve understanding of the degradation processes that dictate the operation lifetime of solid oxide cells (SOC). Transforming our society to rely only on sustainable energy sources is a formidable