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Field
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programme Is the Job related to staff position within a Research Infrastructure? No Offer Description → Apply before 10/12/2025 (DD/MM/YYYY) 23:59 (Brussels Time) → Faculty of Engineering and Architecture
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FieldComputer scienceYears of Research ExperienceNone Research FieldMathematicsYears of Research ExperienceNone Additional Information Eligibility criteria The candidate must hold a PhD in computer science (or a
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at the intersection of AI, NLP, and industrial applications. Contribute to the development of scalable and interpretable AI tools for real-world deployment. Qualifications: A PhD in Computer Science, Machine Learning
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, technical reports, and presentations. Seek membership and service opportunities in professional, academic, and research organizations. Basic Qualifications: A PhD in computer science/engineering or relevant
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in international research visits if needed. We are looking for a highly motivated researcher with: A PhD in machine learning, computer vision, remote sensing, glaciology, climate science, or a related
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. * Applicants who have not yet completed their Doctoral degree are welcome to apply, provided that the degree will be awarded no later than June 15, 2026. Has experience with computational methods, programming
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for AI and deep learning (details: NVIDIA DGX-2) Intel-based Aurora Supercomputer: A next-generation supercomputing system (details: Aurora Supercomputer) Additional advanced compute architectures designed
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be an effective communicator, multitask, and work well on collaborative and interdisciplinary designs. Specific Requirements Education PhD in Computer science obtained between one and two years before
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2026 - 12:00 (UTC) Type of Contract Temporary Job Status Full-time Is the job funded through the EU Research Framework Programme? Not funded by a EU programme Is the Job related to staff position within
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PhD in biochemistry, biophysics, chemistry, computational biology, or a related discipline. solid coding foundation and understanding of protein design pipeline knowledge of computational pipelines