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. About the lab and St. Jude: Successful candidates will work closely with Dr. Chen to develop a personalized career development plan tailored to their long-term goals. Our lab is deeply committed
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iNANO at Aarhus University is seeking a postdoctoral fellow for the Novo Nordisk Foundation CO2 R...
Researcher Development Programme targeted at career development for postdocs at AU. You can read more about it here . At the Faculty of Natural Science at Aarhus University, we strive to support our scientific
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Assistant/Associate Professor at the interface of chemistry, biology & medicine(computational focus)
this department in a manner that is consistent with standard practices for tenure-track faculty within that department. The candidate will also be expected to develop a world-class research program in molecular
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, team-wide support in daily operations; hands-on training and mentorship. Access to world-class researchers, resources, and impactful science as part of your career development. The opportunity
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(mechanical, electromagnetic, and, possibly, fluid-dynamic) and multi-scale simulations for drone components using finite element tools (e.g., Abaqus, Comsol). · Supporting the development of an AI
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plan and their translation into specific business initiatives. Leads and facilitates IS leadership in developing integrated solutions for transformation that include new programs, procedures, and
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teams to support strategic program campaigns. Develop and deliver crisis communication training for leadership, Incident Command Teams, and other stakeholders. Conduct simulations and tabletop exercises
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to mentoring and be strongly motivated to develop a transformative collaborative research program at St Jude. To apply: Interested candidates should submit a cover letter, a 3-5-page summary
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to mentoring and be strongly motivated to develop a transformative collaborative research program at St Jude. To apply: Interested candidates should submit a cover letter, a 3-5-page summary
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Robotisation (PROMAR) group, headed by Matthias Rupp. The group develops fundamental and technological expertise in machine learning for materials science, including data-driven accelerated simulations and