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on “Maternal Immune Activation” involving the development of novel artificial intelligence methods (graph and geometric deep learning, LLMs, …) working on methods for predictive multi-omics integration
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resilience and its change over time in the past (based on Earth observation data), present and future (based on Earth system model simulations for different future scenarios, e.g. using the CMIP6 ensemble and
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proteins with regard to their role in the development of cancer, the emergence of therapy resistance, as predictive markers to guide therapy and as therapeutic targets. Your Responsibilities Independent
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, predict, and treat diseases. You will work with multimodal biomedical datasets including omics, imaging, and patient data and apply cutting-edge AI models such as graph neural networks, transformer
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research. For European Union HORIZON Action Grant Budget-Based agreement project PREVENT - Im-proved Predictability Of Extremes Over The Mediterranean From Seasonal To Decadal Timescales - PIK is offering a
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Researcher / Postdoc for molecular investigations on microbial ecology in deep-sea polymetallic n...
generation, gene/genome reconstruction, prediction of phylogenetic domains of DNA sequences and genes, molecular feature classification, and protein clustering based on structure and function. Skills in R