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simulations for plume-in-grid models Requirements: university degree (MSc or equivalent) in the field of aerospace engineering, physics or similar solid knowledge of Physical and Analytical Chemistry (phase
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modeling and computational workflows Knowledge about machine learning: statistics and deep learning Experience in data analysis, visualization and presentation Good programming skills in languages such as
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well as material characterization would be beneficial basic knowledge of plasma physics, thin-film technology, and semiconductor physics would be an advantage fluency in English - written and oral We offer: You will
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Description The International Max Planck Research School “Knowledge and Its Resources: Historical Reciprocities” (IMPRS-KIR) invites applications for 3 doctoral positions, to begin on September 1
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related field research experience, evidenced by publication(s) or a relevant M.Sc. thesis, good knowledge of algorithms and discrete mathematics excellent written and spoken English skills knowledge
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tolerance of these novel materials and to enable a knowledge-based assessment of their suitability for future nuclear systems. At the same time, the successful candidate will contribute to maintaining
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the existence of a degree of severe disability in your cover letter or resume. The HZI is actively committed to equality, diversity and integration. For this reason, the HZI pursues the goal of professional
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, maths, or a similar field A strong background in one of the biological disciplines covered by PRIDAS (behavioral biology, data science, neuroscience, physiology, genetics) Knowledge of at least one
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experience with methods of molecular biology and/or in the field of histology Experience in animal experimentation is an advantage Knowledge of statistical methods for data analysis Very good written and
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analysis using microscopy and time-resolved spectroscopy, testing reusability of heterostructures, dielectric engineering concepts, and join work with sustainability experts; acquiring knowledge and tools