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students who are eager to develop and apply artificial intelligence techniques and mechanistic mathematical models to explore fundamental questions in biology. The PhD program is organized in partnership
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the energy transition in Luxembourg by co-creating an ambitious research program. It will utilize a data-driven approach to support decision-making for an optimal energy system, with specific focus on cost
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to accelerate the energy transition in Luxembourg by co-creating an ambitious research program. It will utilize a data-driven approach to support decision-making for an optimal energy system, with specific focus
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/electrical engineering, or a related field.Strong interest in automation and laboratory robotics.Basic experience in wet-lab microbiology techniques.Willingness to learn programming and computational analysis
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considered a strong asset. Experience with cybersecurity and programming. Communication Skills: Proficiency in written and oral English (French is considered an advantage) Good academic writing Strong interest
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post-doctoral researchers from diverse backgrounds (e.g., economics, engineering, computer science, information systems, etc.), united in pursuit of sustainable solutions that positively impact and shape
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diverse academic backgrounds to contribute to our projects in areas such as: Network Security, Information Assurance, Model-driven Security, Cloud Computing, Cryptography, Satellite Systems, Vehicular
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in a dedicated training plan For further information, please contact Prof. Marcus Völp at critix- Your profile Qualification: Master in Computer Science and/or Cybersecurity or equivalent degrees with
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bioinformatics and computational biology Strong interest in immune-brain interactions and food allergy-related immunology Excellent communication skills and fluency in English A collaborative mindset and
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degree or equivalent in Robotics / Aerospace / Mechatronics / Mechanical or Electrical Engineering, or related fields in Engineering or Computer Engineering Programming Skills: Design tools for Mechanical