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learning, deep learning, and large language models (LLMs), for the analysis of high-throughput multi-omics datasets (especially single-cell and spatial omics) and large textual corpora (e.g., scientific
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within our portfolio of hypothesis-generating screening studies, a methodological portfolio where we identify signals of interest from real-world register data to guide the conduct of tailored studies. We
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Area of research: Scientific / postdoctoral posts Job description: Postdoc for "Large-Eddy Simulations of Arctic air-mass transformations" (m/f/d) Background The Arctic climate is shaped by
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live in. Your role The CLAIM and ICR groups are seeking an outstanding postdoc to strengthen their research teams with expertise in Large Language Models, more precisely in Agentive Reasoning and LLM
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microscopy data analysis, chemometrics, and machine learning. This position is ideal for a researcher who enjoys working at the interface of imaging, data science, and environmental monitoring. The project
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encourage all qualified candidates, regardless of background, to apply! Job description The candidate will work on large-scale data analysis of cancer transcriptomics data (bulk, single cell and spatial), and
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huge data storage capacity to accelerate the research performed in intensive computing and large-scale data analytics (Big Data). This characteristic distinguishes the HPC center at the university from
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machine learning. The research at DTU Bioinformatics is focused on bioinformatics and computational analyses of large amounts of data generated within biological, biomedical and biotechnological and life
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generating, mobilising, and harvesting “big data” to create a dynamic and agnostic collection of information and deliver a new class of research that will enable a better understanding of the clinical
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research is based on large and high-dimensional datasets across multiple modalities, including molecular, clinical and histopathology imaging data. Our computational pathology research is based