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theoretical methods shall be employed. A solid background in quantum mechanics and programming skills are prerequisite for this position, as is the readiness to learn and to apply new methods. For an initial
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models. Requirements The successful applicants will have: A solid computational background, an interest in cognitive neuroscience a and strong deep learning programming skills. Ability to work in an
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of the strongest research environments for basic plant research in Europe. Research at UPSC covers a wide range of disciplines in plant biology including ecology, computational biology, genetics, physiology
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of the (computational) mechanics of solids and the finite element method and/or spectral solvers Practical experience in at least one programming language (preferably Python) and experience with the use of Unix/Linux
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skills Experience with nanoparticles for drug delivery or diagnostic applications Familiarity with biological systems and cellular targeting mechanisms Knowledge of computational tools for modelling
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influence its development directly. We are currently evolving our mechanical engineering degree program and constructing labs to support both educational activities and research. Workplace description
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, NTNU. This PhD position is financed via the European Research Council’s Advanced Grant Program. The candidate needs to fulfill the requirements of NTNU for obtaining a PhD. The appointment has a duration
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, biomechanics and computational approaches. A relevant background is a degree in plant biology and/or related fields. Other requirements are: Solid background in cell and molecular biology. Experience in standard
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Research theme: Applied Mathematics, Continuum Mechanics, Liquid Crystals Application deadline: All year round The successful candidate will join the PhD programme of the Department of Mathematics
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mechanics and solid mechanics Willing to travel and attend the meetings with industrial partners on site; Should have or be willing to work within a multidisciplinary environment. How to apply Interested