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under the Danish Ministry of Science, Technology and Innovation . The application must be in English and include a curriculum vitae, degree certificate, a complete list of publications, a statement of
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molecular biology, protein purification (ideally membrane proteins) Excellent communication skills in English (oral/written) Ability to take ownership and drive projects forward Have a collaborative mindset
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evaluate the importance of structuring the foods of the future. A high level of verbal and written communication in English; Practical abilities to carry out experimental research, and excited to develop new
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. Responsibilities and qualifications The overall aim of the project is to generate new knowledge about how emerging generative AI tools – such as Copilot, speech-to-text systems and retrieval-augmented generation
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Solid programming experience, preferably in Python Familiarity with structured data handling (e.g., SQL) and scientific workflows Documented experience with ontology development, knowledge graphs, and
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evaluate the importance of structuring the foods of the future. A high level of verbal and written communication in English; Practical abilities to carry out experimental research, and excited to develop
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Post Doctoral Researcher in Human-Centered AI for Software Engineering, Department of Electrical ...
particular with Large Language Models. Solid programming expertise in Python. Be the main author in at least one journal publication in the area of AI4SE, published at a high impact journal. Experience with
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at CSIC and UCM in Madrid, as well as Aarhus University, in a joint effort between the ERC Synergy project METRIQS and the Villum Young Investigator programme DynamiQ. Responsibilities and qualifications In
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language models (LLMs) for educational purposes. Furthermore, the right candidate has a deep understanding of pedagogical research, with focus on how educational processes can be facilitated by AI. The role
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, TESPy, or similar libraries. Strong programming skills in Python or MATLAB, including use of scientific libraries (e.g., NumPy, Pandas, Matplotlib, etc). Experience with machine learning (e.g., Scikit