259 modelling-and-simulation-of-combustion-postdoc Postdoctoral positions at Nature Careers
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tendon models ("tendon-on-chip"), this will provide a powerful system to investigate the complex mechanobiology of tendons. Particular focus will be given to neurotendinous crosstalk and its
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transduction, cell culture, and immune functional assays; supporting the development of in vivo models, such as adoptive T-cell transfer in mice, for preclinical testing of engineered circuits where relevant
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leadership positions. We, among others, do this through our gender equality plan and the cascade model measures, which we actively implement to enable sustainable equal opportunities in academic career paths
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Hospital. It hosts the residency and PhD programs of Humanitas University , a life science university that stands out for its real-world simulation-based approach to medical training and its international
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and in silico techniques. informatics/AI modeling approaches. identifying new therapeutic targets for chronic disease. Key responsibilities include : planning, organizing, performing, and monitoring
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us. Gender equality is an important aspect for us. To support work life balance we offer flexible working hours, variable part-time, job-sharing models and participation in mobile work (up to 50%). You
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supporting diversity at our centre, we actively promote women in science and in leadership positions. We among others do this through our gender equality plan and the cascade model measures which we actively
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letter (max 1 page) describing your research interests and qualifications, Curriculum Vitae (CV) with a list of publications and technical competencies, Certified copy of doctoral degree certificate and
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and/or insect cell culture. Prior experience with single-molecule biophysical techniques, GPCR biology, or quantitative modeling. Significant contribution towards peer-reviewed research articles in
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Python is required. Programming in C or C++ is a plus. Background in statistical genomics, longitudinal modeling, non-parametric statistics, machine learning and deep learning are preferred and encouraged