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, dynamic simulation, additive/classical fabrication; sensorization, actuation, and integration on gantry/field robots. For PhD#3 (DT): Design software architecture; integrate multi-modal data and models (e.g
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LLM-based vulnerability detection systems. Robustness evaluation framework: you will develop comprehensive assessment methodologies to quantify the weaknesses and limitations of LLMs in software
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school. Follow the instructions on the web page English language requirements for doctoral education. Verification of your documents Karolinska Institutet checks the authenticity of your documents
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efficiency, developing knowledge, methods, and transferable software for the simulation and comprehensive sustainability assessment of socio-economic systems. Its purpose is to foster sustainable eco
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Reliable Software Engineering and Decision-Making (SerVal) group at the University of Luxembourg. SerVal conducts research in security and reliability in software engineering, with a particular focus on AI
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-cell imaging) or image analysis software (e.g., Fiji/ImageJ). Advanced Cell Manipulation (e.g., genome editing via CRISPR/Cas9, flow cytometry/FACS). Basic familiarity with data analysis tools (e.g
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research record with publications in relevant venues (AI, security, and software engineering conferences/journals) Strong analytical and problem-solving abilities, with capacity to conduct independent
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. Developing software tools compatible for integrated use with popular data analysis packages, to be made available for public distribution. Eligibility Essential: Relevant Master’s degree (see notes below) in
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engineering Knowledge of machine learning (deep learning) Basic knowledge of computer science or software development, e.g., using Java, Python, or C++ Good communication and information skills, goal-oriented
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bioinformatics including NGS (Nanopore, Illumina, PacBio) Experience with automation and coding in Python or other programing languages Experience with protein software tools like AlphaFold3, Boltz2, PyMOL