27 machine-learning-"https:"-"https:"-"https:"-"UCL" uni jobs at Nature Careers in Germany
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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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. Demonstrated scientific expertise in immunogenomics, antigen discovery, and machine learning/AI applications in biomedical research. Strong proficiency in the analysis of next-generation sequencing (NGS) data
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machine learning. A special emphasis will be placed on the correlative combination of the experimental capabilities of scanning electron microscopy (SEM), electron probe micro analysis (EPMA), transmission
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. Responsibilities include: Managing and mentoring a multidisciplinary team of machine learning and image analysis experts Coordinating DCU activities across partner sites and aligning them with HI strategy Co
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team — comprising biologists, engineers, computer scientists, and medical researchers — develops next-generation computational models to interpret complex biomedical data across multiple scales. Our
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connecting AI, computational biology, human–computer interaction, and research software engineering. Close collaboration with the Helmholtz AI Consultant Team, providing direct exposure to a broad range of
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, engineers, computer scientists, and medical researchers — develops next-generation computational models to interpret complex biomedical data across multiple scales. Our innovations in tissue clearing, 3D
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, engineers, computer scientists, and medical researchers — develops next-generation computational models to interpret complex biomedical data across multiple scales. Our innovations in tissue clearing, 3D
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the organization. Your profile Bachelor's or master's degree in computer science, computer engineering, cybersecurity or a related field and relevant security certifications (e.g., OSCP, CCSP, CISSP, CISM) from a
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are modern instrumental drug and bio analytics, development and characterization of macromolecular drugs, development and application of computer-aided drug design methods, and structure-guided drug design