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manage research projects, ensuring alignment with institutional research objectives Supervision of research assistants, graduated and exchange students Key Competencies and Educational Qualifications: PhD
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-tier venues (e.g., ICSE, ASE, TOSEM, AAAI, EMSE), with at least 10+ publications, including multiple CORE A/A* papers. Demonstrated expertise in deep learning architectures, computer vision, and medical
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challenges. Key Responsibilities: As an early-career researcher developing your academic profile, you will be expected to: Conduct cutting-edge research in areas aligned with the group's research agenda
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effectively to academic, policy, and practitioner audiences. Act as a key liaison between interdisciplinary collaborators, ensuring smooth communication and alignment of deliverables. Track progress against
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a focus on emerging threats, adversarial resilience, and trustworthy autonomous decision-making. Design and implement novel research methodologies to advance the security, reliability, and alignment
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interdisciplinary teams to align AI research with ethical standards and best practices in AI safety. Publish findings in top-tier conferences and journals, contributing to the broader AI and machine learning research
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research that covers the energy value chain from generation to innovative end-use solutions, motivated by industrialisation and deployment. ERI@N has multiple Interdisciplinary Research Programmes which
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network with leading universities globally. The on-campus concept provides a structured approach focused on applied research in strategically important topics aligned with Schaeffler’s strategic roadmap
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Ability to code in a programming language to solve computational problems Awareness of computational infrastructure and its upkeep Ability to work on multiple projects in parallel and set priorities
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for activating small molecules such as CO, CO2, or syngas. Depending on experience, the candidate may also lead independent research projects aligned with the team’s scientific objectives, while assisting in daily