36 high-performance-computing-postdoc PhD scholarships at University of Southern Denmark
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Computer Vision There is growing trend towards explainable AI (XAI) today. Opaque-box models with deep learning (DL) offer high accuracy but are not explainable due to which there can be problems in
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Job Description The Department of Mathematics and Computer Science (IMADA) at the University of Southern Denmark, Odense, invites applications for a PhD position in algorithms. The position has a
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to fundamentally revisit the way that we define and quantify the value of our built environment. This fully funded PhD project is part of a Marie Sklodowska Curie Action Doctoral Network, QuiVal, a programme funded
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PhD Positions Country Denmark Application Deadline 14 Dec 2025 - 23:59 (Europe/Copenhagen) Type of Contract Temporary Job Status Full-time Is the job funded through the EU Research Framework Programme
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computer science. The candidate is expected to have solid knowledge in most of the following areas: Robotics Control theory Deep Learning & Machine learning Modelling and control of soft/continuum robots Experience
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for SSM-SNN cores Integrate RISC-V processors using SoC flows Perform full-chip simulation, verification, and prototyping Publish and present research in high-impact venues Qualifications Applicants should
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2026 Is the job funded through the EU Research Framework Programme? Horizon Europe - MSCA Is the Job related to staff position within a Research Infrastructure? No Offer Description The Department
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the candidate will work under the DANARC project that aims to develop a robotic-based system capable of autonomously performing cardiac ultrasounds. The starting date will be agreed with the successful candidate
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computers, one of the major milestones is the development of high-quality quantum bits (qubits), the core units of quantum computation. Unlike classical bits, solid-state qubits must operate at extremely low
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to work on investigating how sex-dependent low-grade systemic inflammation caused by MetSy affects neurological outcome in IS patients. This will be performed in clinical cohorts, using clinical and