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LMU Munich. The group is located within the Institute of Clinical Neuroimmunology (https://www.neuroimmunology-munich.de/ ). The professorship of Systems Neuroimmunology is part of the Cluster
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. Our mission is to move beyond descriptive biology and develop predictive, mechanistic models that connect molecular regulation to cellular and systems-level phenotypes. The Laboratory of Computational
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citizens in their choices, public authorities in their decisions and businesses in their strategies. Do you want to know more about LIST? Check our website: https://www.list.lu/ How will you contribute
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exist. To address this knowledge gap, in the BUG-ID consortium, seven European universities, one research institute, one hospital and six private companies have teamed up. Our consortium will train 15
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on the evolution of gene regulatory networks and Wnt pathway functions in emerging model organisms (e. g. insects, annelids, snails, flatworms, cnidarians), utilizing ‘omics technologies and bioinformatics. Students
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Smet ( https://desmetlab.sites.vib.be ) and F. Van Breusegem ( https://vanbreusegemlab.sites.vib.be ) have expertise in abiotic stress signaling and in advanced molecular profiling, including mass
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The Leibniz-Institut für Analytische Wissenschaften - ISAS - e. V. develops efficient analytical methods for health research. Thus, it contributes to the improvement of the prevention, early
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bioprocess optimization. The successful candidate will contribute to the development of sustainable bioconversion platforms for the transformation of biogas-derived carbon into amino acid-enriched biomass
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DTU Tenure Track Researcher on Nanoreactors for Operando Visualizations of Nanoparticle Catalysis...
microscopy for nanoparticle catalysis at the Center for Visualizing Catalytic Processes (VISION). Responsibilities and qualifications You will engage with VISION’s development and application of nanoreactors
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SD- 26053 PHD IN ULTRA-FAST MACHINE-LEARNING INTERATOMIC POTENTIALS FOR NANOINDENTATION OF TIC MA...
PhD candidate to develop and apply ultra-fast machine-learning interatomic potentials (UFPs, Xie et al., npj Comput. Mater., 2023, 10.1038/s41524-023-01092-7 ) for long, multi-million-atom molecular