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cybersecurity allowing thus to validate and receive feedback from on-the-field cybersecurity practitioners. As generative AI (GenAI) platforms and large language models (LLMs) are increasingly integrated
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cybersecurity allowing thus to validate and receive feedback from on-the-field cybersecurity practitioners. The PhD candidate will investigate how AI and above all Generative AI (GenAI) can be leveraged
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into this material and support tailoring its properties. For this, you will: Contribute to method development for ultra-fast MLIPs (Xie et al., npj Comput. Mater., 2023) Develop realistic MD simulation protocols
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developments such as AP/MALDI-2. Is Your profile described below? Are you our future colleague? Apply now! Education PhD in chemistry, biology or related field Experience and skills Background in analytical
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cybersecurity allowing thus to validate and receive feedback from on-the-field cybersecurity practitioners. As generative AI (GenAI) platforms and large language models (LLMs) are increasingly integrated
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Qualification: The candidate should possess a MSc. Degree or equivalent in Engineering, Computer Science, or related fields. Experience: The ideal candidate should have some knowledge and experience
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the development of both, the quantum internet and distributed quantum computing. The objectives of this PhD thesis project are: (a) Demonstrate spin-photon entanglement with single colour centres in silicon carbide
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Qualification: Master in Computer Science and/or Cybersecurity or equivalent degrees with expertise in at least one of the above areas (dependability, real-time systems, operating systems
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, Large Language Models, Human-Computer Interaction, Virtual reality. The selected candidate will work on the design and implementation of a human-computer interface to support education using an AI-based
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spin-photon entanglement. With this milestone demonstration, we strive to kickstart subsequent developments towards a quantum internet architecture. The objective of this PhD thesis is to demonstrate