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users: provide project consultation, training and hands-on support, schedule and prioritize measurements, and ensure timely data delivery Drive method development for single-cell MSI and integration with
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prevention of human diseases (e.g., Li et al., Nature Metabolism, 2024; Ni et al., Cell Metabolism, 2023; Leung et al., Science Translational Medicine, 2022; Seelbinder et al., Nature Communications, 2023
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and analysis of mathematical methods for novel imaging techniques and foundations of machine learning. Within the project COMFORT (funded by BMFTR) we aim to develop new algorithms for the training
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variants on human traits and single-cell readouts. Our research group is pioneering computational methods for deciphering molecular variation across individuals, space, and time. We have a track record in
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, initiative/commitment, ability to work in a team and willingness to cooperate, willingness to learn We offer: Interdisciplinary research at the interface of politics, economics and society Work in national and
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reduction, uncertainty quantification, machine learning, fluid mechanics. Experience with scientific object-oriented programming languages (C++, Python, or Julia) is highly relevant. Knowledge
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areas is expected: numerical analysis, scientific computing, model reduction, uncertainty quantification, machine learning, fluid mechanics. Experience with scientific object-oriented programming
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to the development of personalized microbiome-based strategies to aid in the detection, monitoring, treatment, and prevention of human diseases (e.g., Li et al., Nature Metabolism, 2024; Ni et al., Cell Metabolism
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of these patients. The goal of this project is to combine cutting-edge multi-omics technology, data analytics, machine learning and clinical samples from the human eye to decipher new insights into disease mechanisms
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following position Postdoctoral researcher (m/f/d) in Environmental Data Science and Machine Learning for the project BoTiKI Location: Görlitz Employment scope: full-time (40 weekly working hours) / part