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to generate reproducible, micrometer-scale controllable, and cost-efficient disease models by bringing together experts in molecular systems engineering, machine learning, biomedicine, and disease modeling
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-dimensional cell cultures are important to enable realistic cell environments for disease modeling and to analyze cell interactions. This position will address the question of how one can develop minimally
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Your Job: We are looking for a researcher to develop and apply machine learning models for genomic data in our lab. We focus on sequence analysis, genomics, semantics, and cross-domain data
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Excellent skills in statistical modelling, preferably using R Proven track record of publishing in international peer-reviewed journals as first author Willingness to conduct fieldwork and participate in
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plan that focuses on the development and combination of 3D-generative models and potency predictions for drug design. A successful research proposal to our question will focus on these topics: How
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. For modeling, we use both public and proprietary clinical and research data and generate our own repository of digital pathology images. A further focus of our lab is the improvement of digital pathology
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(including the doctoral dissertation) Strong methodological training in quantitative survey and experimental research (Additional asset: experience with using large language models in surveys) Proficiency in
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of in vitro and in vivo pre-clinical models, including hiPSC-derived systems The postdoctoral project will combine experimental (wet-lab) and computational (dry lab) approaches Be part of Geman Center
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Postdoc position: mechanisms of autoimmunity & autoinflammation in inborn errors of immunity (m/f/d)
erythematosus (SLE). This project will integrate biochemical, immunological, and imaging techniques, along with co-culture of patient-derived organoids and model organisms combined with various –omics approaches
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The Network Analysis and Modelling group investigates how genetic variation shapes gene regulation, protein function, and, ultimately, observable plant traits. Using machine learning and network