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ICT Services & Applications. Your role We offer a fully funded PhD student position within the Trustworthy Software Engineering (TruX) Research Group headed by Prof. Dr. Tegawendé F. Bissyandé
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working with deep learning software stacks, extensive software development experience, and knowledge of machine learning frameworks (such as transformers, torch, Megatron, triton etc.) are pluses. MSc
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software as python packages Reporting findings and methods in conference and journal papers Your profile Masters, Diploma or equivalent degree in IT/computer science/statistics/applied mathematics/data
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data scientists, software engineers, biomedical researchers, and clinicians. Your research will focus on developing AI- and LLM-enabled methods and tools to structure, harmonise, and analyse clinical
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micro to laminate/structure), including automation, verification, and clear post-processing metrics for stress concentration reduction. Investigate surrogate modelling (AI/ML) to accelerate the micro
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research and aims to advance inclusive, robust, and scalable multilingual AI systems. TruX conducts research in software security, software repair, and explainable software to create key practical solutions
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Coupling of physics-based and data-driven models, studying when and how to switch between them in real time Integration with ARSPECTRA's software stack, e.g. marker tracking, SLAM, gaze tracking, and
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software engineering, computer science, data science, bioengineering, bioinformatics, engineering, physics or related Experience in either machine learning or computational biology. Interest in both
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experience (e.g. student assistant post) • Preferably demonstrable experience in academic writing for publication (e.g. first or co-authored peer reviewed papers) • Well-developed statistical software skills
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the development of scalable software tools and pipelines, potentially leveraging GPU/FPGA accelerators. Our aim is to build next-generation molecular atlases for chronic diseases and to improve patient