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manufacturing", new AI methods for predicting the outcome of AM printing processes under varying bounding conditions are developed. This involves the design of a cyber-physical system incl. a data management
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PhD doctoral candidate (d/f/m) Predictive Tissue Medicine Specialty Pathology Apply now Work time part-time Start date Now Employment period limited Application deadline 18.12.2025 Deployment
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Fraunhofer Institute for Wind Energy Systems IWES | Bremerhaven, Bremen | Germany | about 2 months ago
10 Oct 2025 Job Information Organisation/Company Fraunhofer Institute for Wind Energy Systems IWES Research Field Engineering » Mechanical engineering Researcher Profile First Stage Researcher (R1) Positions PhD Positions Country Germany Application Deadline 26 Oct 2025 - 23:59...
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Who we are ... At the Fraunhofer Institute for Wind Energy Systems IWES, the energy transition becomes a reality every day. Our focus topics are: offshore wind energy, hydrogen, test infrastructure and digitization. More than 400 employees – including around 100 students – from over 50 countries...
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crop production systems. The project will focus on integrating high-resolution drone-based remote sensing data, including multispectral and thermal imagery as well as LiDAR measurements, into ensemble
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build a computational model of SIHUMIx to predict new interactions and how the community reacts to disturbances—predictions that will later be tested in bioreactor experiments This work will give us a
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health and disease. Our focus is to establish both preclinical validation models for Microbiota-based therapeutics, conduct clinical trials and use clinical datasets to develop prediction models
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evolve and stabilize during symbiont establishment. Model-based predictions will be further refined and experimentally tested, ensuring an iterative exchange between in silico and in vivo approaches. Key
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PhD student (m/f/d) in the field of chemistry, chemical engineering, materials science or comparable
of the target materials based on the characterization results Using in silico pre-screening and synthesizability predictions to generate lead candidates for the synthetic exploration Reporting, documentation, and
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therapeutics by protein design. This project will apply cutting-edge generative AI methods—including protein design, structure–function prediction, and multimodal learning—to develop and optimize a new