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toxicological prioritization. Developing non-target analysis to capture vPvM chemicals, combined with toxicological effect-directed in-vitro screening is essential. This approach supports comprehensive hazard
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providing a structured, semantic framework that enhances knowledge sharing and data reuse across different platforms and systems. Project Aim This PhD will develop an ontology-based methodology to improve
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obtaining academic qualifications as well as courses on development of competences at university as a workplace and orientation with regard to further career steps in science, industry and society
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The Faculty of Engineering, Department Elektronica en informatica, Research Group Electronics and Informatics: Research – Development - Innovation is looking for a PhD-student with a doctoral grant
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Project descriptionAutonomous systems are intelligent agents—such as robots, vehicles, or drones—that can sense their environment, make decisions, and act independently. When multiple such agents
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workstreams, and the PhD’s will be working along senior staff to perform tasks in different workstreams, in strong collaboration with multiple international partners and fellow PhDs from all over the world. Key
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of sample processing and method development with multiple contract research organizations relating to toxicity, ADA and sample storage/labelling/stability studies will also be key responsibilities
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actively contribute to this strategic initiative by researching and developing scalable, practical frameworks for implementing Trustworthy AI principles in diverse projects and across multiple technology
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candidate may vary and will ultimately depend on multiple factors, which may include the successful candidate's geographic location, skills, work experience, internal equity, market conditions, education
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-time 65%) in the DFG-funded Integrated Research Training Group (RTG) Beyond Amphiphilicity – RTG 2670: Self-Organization of Soft Matter via Multiple Noncovalent Interactions . The position is funded from