20 power-engineering-"https:"-"https:"-"https:"-"https:"-"https:"-"https:" positions at VIB
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for society. With the launch of VIB.AI, we are expanding our mission to harness the power of artificial intelligence for life sciences research, innovation, and impact. We are now looking for a Machine Learning
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for society. With the launch of VIB.AI, we are expanding our mission to harness the power of artificial intelligence for life sciences research, innovation, and impact. We are now looking for a Machine Learning
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We are seeking a motivated PhD student with a background in protein engineering, structural biology, chemistry or biophysics to join our efforts in designing and characterizing membrane proteins
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innovations and the biological discoveries they enable Your profile You have: a PhD in engineering, computer science, mathematics or a related field a strong background and proven experience in machine learning
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an excellent reputation in technology transfer. VIB Technologies constitutes the centralized scientific research infrastructure of the institute and allows scientists access to high-end and innovative
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fundamental research and real-world impact through industry partnerships, technology transfer, and the creation of innovative biotech ventures. Our discoveries contribute to new diagnostics, therapies
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. sequencing, single-cell, or spatial data), enough to judge whether an AI-generated analysis makes sense. Ability to explain AI concepts and their limitations clearly to non-specialists. Willingness to keep
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stakeholder engagement initiatives. What we are looking for A genuine interest in life sciences and the ability to engage confidently with researchers and scientific topics. Ability to build trusted
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team and independently You have a strong ability to multi-task and meet deadlines You enjoy other cultures and are respectful of others and their different ideas/opinions We offer Opportunity
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supervision and guidance Desired Profile Experience with neurodegeneration and aging research. Familiarity with secure data infrastructures and FAIR data principles. Ability to combine scientific depth