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We are seeking a highly motivated PhD student to perform fundamental research and to conceive truly sparse solutions (on both, CPU and GPU) for dynamic sparse training, aiming to cut the training costs and energy requirements of state-of-the-art deep learning models significantly, while...
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SD-26045-RESEARCHER IN ADVANCED PLASMA-ASSISTED DEPOSITION PROCESS DEVELOPMENT FOR CATALYTIC THIN...
between Luxembourg and France, the FNR-funded postdoctoral researcher will conduct research in the development of advanced plasma-assisted thin film deposition processes for catalytic and
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! ESRIC is conducting activities in three main areas: Research and testing facilities, Business support and incubation, and Community management. The primary objective of ESRIC is to research, develop and
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. Finally, the research will develop efficient algorithms and test them on realistic networks and using real data from energy and public transport operators. The Doctoral student is also expected
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for Digitalization. This project aims to advance privacy-preserving techniques for data analysis and task automation, ensuring robust protection of sensitive information. The focus will be on developing
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shape the project’s success: Adversarial attack development: you will design and implement problem-space adversarial attacks against LLM-based vulnerability detection systems. Robustness evaluation
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research agenda on trustworthy, data-driven software engineering and AI-assisted development. The successful candidate will work on Bug Report Intelligence for the Generative AI Era (BRIDGE) — exploring
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Alzheimer’s and Parkinson’s. You will work within a multidisciplinary environment alongside data scientists, software engineers, biomedical researchers, and clinicians. Your research will focus on developing AI
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agenda on multimodal and multilingual language models. The successful candidate will focus on the development of multimodal, multilingual resources and on the design and evaluation of methods that leverage
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detection and automation. The UMLFF project aims to develop next-generation MLFFs with built-in uncertainty predictions to enable safe, automated active learning and create broad, reliable MLFFs. You will