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engineering, with a particular focus on AI, data science and decision-making The candidate's research will focus on code quality assurance, code analysis and more generally on the engineering of TrustWorthy
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researcher should have expertise in materials/mechanical/electrical engineering with an excellent understanding of fluid mechanics as well as experience with Arduino/Raspberry Pi programming, 3D printing and
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Computer Science, Information Theory, Physics or related fields High level of mathematical maturity Experience with topics related to quantum LDPC codes and decoding algorithms, or demonstrated ability and
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information systems engineering. The group conducts research on the application and the impact of digital technologies like DLT/Blockchain, Digital Identities and Machine Learning/AI on organisations from both
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integrate your code into their workflows. The preferred starting date is 1 December 2025. Profile You hold a PhD in Computer Science, Physics, Engineering or a discipline equally relevant to the topic
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researcher to join our enthusiastic and young interdisciplinary teams of Prof. Dmitriev (Tissue Engineering and Biomaterials Group) and Prof. Vergult (Functional Genomics lab), as part of the MINDFUL research
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apply: Strong interest in Social Justice, Criminal Procedure, Legal Theory and Human Rights preferably with a specialisation on the use of Artificial Intelligence in Governance and Justice Proven ability
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Engineering, or Electrical Engineering or Computer Science/engineering with a focus on network communications Good understanding of the 3GPP 5G radio access and core network protocols Proficiency in multiple
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-scale screens to study fundamental principles in molecular and complex trait genetics using microbes as model systems. Our core technology MAGESTIC (https://doi.org/10.1038/nbt.4137 ), a CRISPR/Cas9-based
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-scale screens to study fundamental principles in molecular and complex trait genetics using microbes as model systems. Our core technology MAGESTIC (https://doi.org/10.1038/nbt.4137 ), a CRISPR/Cas9-based