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Master Thesis - Development of ligand conjugated lipid nanoparticles for targeted T cell delivery...
Area of research: Diploma & Master Thesis Job description: Master Thesis - Development of ligand conjugated lipid nanoparticles for targeted T cell delivery (f/m/x) 102778 Full time 39 hrs./week
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increasingly important, but also more complex, due to rising demands on performance, precision, quality, and sustainability. Bayesian optimization (BO) - a special machine learning approach - represents a
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or infrastructure. This is what makes our daily work so meaningful and exciting. For the next possible date the German Cancer Research Center (DKFZ) is seeking a Head of an independent Junior Research Group in Target
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analyses, an area in which our group has a track record of success (see recent publications below). The TARGET-AI project seeks to apply leading-edge techniques from deep learning and Bayesian modeling
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Areas (TRA). Creative and visionary contributions to existing and planned integrated research networks are expected. The applicant has an excellent publication record commensurate with their career stage
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and reduction Development and application of big data analytics for large X-ray data sets Application of Bayesian methods to X-ray data Combinatorial analysis of various data from complementary
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processes related to carbon cycling in the soil-plant system Experience with Bayesian inference and machine learning is an asset Ability to work independently and cooperatively as part of an interdisciplinary
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Max Planck Institute for Multidisciplinary Sciences, Göttingen | Gottingen, Niedersachsen | Germany | 20 days ago
the structure from such data is challenging, and new theoretical methods and algorithms are required. The research project aims at deriving priors for Bayesian methods from atomistic simulations and machine
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student's primary field of training, we offer targeted feeder courses that are specifically designed to teach relevant basics to non-specialists. Depending on their background, life science students can take
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development. Experience with implementing statistical learning or machine learning (e.g. Bayesian inference, deep-learning). Programming skills in Python and experience with frameworks like PyTorch, Keras, Pyro