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assigned Requirements A Ph.D. degree in Neuroimaging, Biomedical Engineering, Electrical Engineering, Physics, Computer Science, or other related disciplines, with experience or keen interest in processing
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energy transfer, developing and employing computer simulations, laboratory experiments, and field analyses. Our aim is to gain fundamental insights and develop sustainable technologies to address societal
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The Faculty of Engineering at Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU) invites applications for an Assistant Professor of Machine Learning in Digital Health (salary group W1
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their efforts on the education of students and the performance of life-changing research across a wide range of disciplines including medicine, engineering, physical sciences, energy, computer science, and social
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prototype models from blueprints, schematics, or sketches. Conduct functional and operational tests to evaluate performance and reliability of prototype or production models. Work with engineers to perform
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Starting Date 1 Jun 2026 Is the job funded through the EU Research Framework Programme? Horizon Europe - ERC Reference Number 101220359 Is the Job related to staff position within a Research Infrastructure
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; multidisciplinary researchers who continue to push the boundaries of innovation in physics and engineering to develop cutting-edge methods for enhanced anatomic and functional imaging; staff who are dedicated and
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their application to many areas of physics, materials science, biology, earth science, as well as imaging and data science. There is a strong cohort of activities on applied and computational mathematics
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Engineering within three months of your employment contract start date, and that you participate in an organized doctoral programme through out the period of employment. The position is conditional on external
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, quantitative image analysis) Computational skills in data processing and statistical analysis; experience with sc/snRNA-seq, NGS, metabolomics, proteomics datasets (R/Python) is highly desirable Demonstrated