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, the Optimized AI team focuses on computing techniques to scale up a wide range of AI approaches and drive the SW-HW-Technology co-optimization. We analyze and implement AI models and software architectures while
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relevance and translational objectives. Contribute to discussions on valorization pathways, including positioning of results for partnerships, licensing, or venture creation. Your profile PhD (or equivalent
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) Positions Master Positions Application Deadline 30 Mar 2026 - 23:59 (Europe/Lisbon) Country Portugal Type of Contract Permanent Job Status Full-time Hours Per Week 35 Offer Starting Date 16 Mar 2026 Is the
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. Systems & Software – proficient level of knowledge of Microsoft Office and/or relevant position software programs. Team Orientation & Interpersonal skills – highly motivated team player with ability
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Posting Title Postdoctoral Researcher – Separations science and engineering for biorefining . Location CO - Golden . Position Type Postdoc (Fixed Term) . Hours Per Week 40 . Working at NLR NLR is
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Biological Engineering Posting Link: https://www.ubjobs.buffalo.edu/postings/61152 Job Type: Full-Time Posting Detail Information Position Summary The Shi group is seeking motivated Postdoctoral Associateswith
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visible research, strong industry links and diverse environment create a collaborative setting where ideas grow into real impact. At the division of Interaction Design and Software Engineering , we design
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the field, with a strong track record of internationally competitive research in line with expectations for the respective career stage. PhD in Computer Science, Mathematics, or Engineering Research expertise
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at The Technical Faculty of IT and Design invites applications for a fully funded PhD stipend in the area of Human-Computer Interaction, generative AI, creativity research and knowledge worker studies. The position
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. You have: A PhD in Computer Science, Machine Learning, Applied Mathematics, Scientific Computing, Data Engineering, or a closely related field. Demonstrated ability to conduct high-quality academic