5 model-driven-development "Integreat Norwegian Centre for Knowledge driven Machine Learning" PhD positions at Heidelberg University
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The successful candidate will develop generative machine-learning methods for amorphous molecular thin films — the supramolecular structures that govern the performance of organic-electronic materials
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in the progression of cardiocrine signals to cardiac fibrosis. Utilizing excellent transgenic mouse models, hiPSC-derived cardiomyocytes in combination with computational approaches for big data
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to develop a new class of therapeutics based on bottom-up Synthetic Immunology. Inflammatory signals lead to epigenetic remodeling that can impact subsequent immune responses. This innate immune memory is
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that nephroprotective effects and improved survival in diabetes and experimental models of sepsis have been demonstrated for anserine and carnosine, underscoring dipeptides as a promising and largely underexplored class
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(www.denkglobaldx.org ), our department hosts a diverse and interdisciplinary team working across diagnostic innovation, clinical and implementation research, mathematical modelling, data science, and health-economic