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international groups developing methods for the analysis of microbiome data (https://statdivlab.github.io/ ). The StatDivLab develops cutting-edge statistical methodology to address the most important
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the supervision of students (interns and/or PhD candidates) -preparation of scientific publications and progress reports -presentation of results at national and international conferences This work will be carried
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to work on the design of novel nucleic acid delivery technologies for ex vivo/in vivo CAR-T cell engineering. The postdoc will assist in the development, optimization, characterization and (ex vivo/in vivo
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, for event reconstruction and classification, including potentially machine learning/AI Interpretation in suitable theoretical models Contribution to software activities that are required for wider use by DESY
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, facilitating impactful multidisciplinary collaboration, scholarly advancement, and the creation of tools and public goods. Requirements Applicants must have (or expect to have at time of appointment) a PhD in
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. Innovative academic offerings include bachelor’s, master’s, post-master’s, DNP and PhD programs that are preparing nurse leaders of today and tomorrow at campus locations in Newark, New Brunswick, and
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for the sustainable planning of wind power in forest landscapes. For more information, see: www.slu.se/forskning/forskningskatalog/projekt/w/windyforests/ Your profile You must hold a PhD in forestry, ecology
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researchers where appropriate. • Contribute to the visibility of the project through publications, presentations and collaborative activities. Where to apply Website https://recruitment.icmab.es/job-list
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Responsibilities Conduct research in computational methods for environmental and engineering applications. Develop and analyze numerical algorithms, reduced-order models, and machine-learning-enhanced simulation
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packaging and e-waste, while Exergy will develop the digital-twin and machine-learning tools that make the process adaptive and scalable. The research effort will be directed towards the selective recovery in