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Computer Science, Software Engineering, Artificial Intelligence, or a related discipline. Strong research track record in software engineering, AI for code, or software security (e.g., publications in
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Ciência e a Tecnologia, is available under the following conditions: OBJECTIVES | FUNCTIONS This task evaluates the impact of controlled code perturbations on the classification stability and robustness
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or coding platforms including SketchUp, EnergyPlus, OpenStudio, TRNSYS, and Python; Proven ability to work at a fast pace and to react rapidly to new information; F1 experience would be advantageous but not
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efficient coding is important. Key Responsibilities: Participate in and manage the research project with Principal Investigator (PI) Ian McLoughlin, Co-PI Tong Rong and the research team members to ensure all
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AI/ML models for predicting materials properties using data-driven approaches, including the treatment of disordered inorganic materials. Develop codes as necessary to assist existing and new code
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European Charter for Researchers, the Code of Conduct for the Recruitment of Researchers and our commitment to achieve fair and transparent recruitment and appraisal procedures. Requirements Additional
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reproducible workflows (code, metadata and documentation) in line with project and UKRI expectations. Prepare research outputs including papers, conference presentations and contributions to shared project
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model validation. Contribute to reproducible modelling workflows (version control, documentation, shareable code and outputs) and participate in production of open research outputs. Support and lead
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box 1072 Blindern Postal Code NO-0316 E-Mail mathias.hudoba@its.uio.no STATUS: EXPIRED X (formerly Twitter) Facebook LinkedIn Whatsapp More share options E-mail Pocket Viadeo Gmail Weibo Blogger Qzone
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Large Language Models (LLMs), integrating dataset expansion, evaluation, incremental fine-tuning, and security-aware code generation validation. The student will build an integrated pipeline that reuses