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-cell or spatial transcriptomics, or digital pathology) Strong programming (Python / R) and analytical skills, with proficiency in bioinformatics tools, statistics and machine learning. Experience with
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colon. The project is funded through the ERC "Unstable Genome". The position is co-supervised by Wolfgang Huber at EMBL and Dr. Aurélie Ernst at DKFZ. The Huber group develops statistical and machine
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motivated PhD students, interns, and PostDocs at the intersection of computer vision and machine learning. The positions are fully-funded with payments and benefits according to German public service
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talents and passion as we work together to drive forward scientific progress. The Institute of Machine Learning in Biomedical Imaging (IML) focuses on pioneering research to harness the power of machine
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for reward funds such as voluntary carbon markets, offset markets, or tax clubs (e.g. on aviation, maritime shipping, or luxury goods). Use of empirical or machine-learning techniques for estimating baseline
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moderation can be exploited by malicious actors to circumvent controls. The research will involve leveraging insights from machine learning on strategic classification and conducting lab experiments to assess
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success rates of real, patient-specific aneurysms, their treatment options, and long-term prognosis. The project is complemented by contributions in machine learning, such as the rapid generation
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areas, notably in Physics-Enhanced Machine Learning, Computer Vision & AI, and AI in Health Care and Medicine.The position is a full-time position (100%), initially for 2 years and 3 months, with
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disciplines with PhD Extensive knowledge of machine learning/artificial intelligence and big data science Extensive knowledge of programming languages (ideally Python) Basic knowledge of synchrotron research
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Technology (CIT) and TUM School of Medicine and Health is offering a 2y-4y postdoctoral full-time position in medical machine learning. The Computational Pathology Lab (https://schuefflerlab.org