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intentionality, emotion regulation). Demonstrated interest in, or prior work on, the emotional capabilities of LLMs or other AI systems. Programming skills in Python sufficient for experimental work and data
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field Interpret large amounts of data Knowledge of statistical packages (e.g., Python, R, SPSS, SAS) Knowledge of data collection methods (polls, focus groups, surveys) Ability to learn and appropriately
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(i.e. machine learning, neural nets, LLMs). Prepare results and design figures for reports and presentations. Manage and manipulate data using requested languages, including Python, R, MATLAB, and STATA
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Brughmans. You can read more about the lab here: https://cas.au.dk/en/social-resilience-lab Tasks: · Mining and extracting structured data from academic literature and historical sources, as well as web
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childhood adversity (Buimer et al., 2025, preprint https://europepmc.org/article/ppr/ppr1071622 ). The project examines how adversity affects social learning and self-esteem, and how these processes
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for object-centric processes using MDE. The foundations of the project have been published in a prior paper, see https://link.springer.com/article/10.1007/s10270-024-01191-z . Given the international research
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. Proficiency in Python and modern deep learning frameworks (e.g., PyTorch). Demonstrated interest in designing and implementing AI systems for real-world applications. You are expected to be somewhat accustomed
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Analysis of open datasets (Big/Open data) Programming skills in commonly used languages (bash, Matlab, Python) High-performance computing (HPC) The primary place of work is Turku, and the selected candidates
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, Biomedical Engineering, or a related field (or equivalent experience). Strong programming skills in Python, with experience in: NLP/LLM frameworks (e.g., Hugging Face, LangChain, opencode,...). Software
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programming skills (Python or R) for data analysis Ability to design and execute experiments independently Strong motivation, scientific curiosity, and drive Ability to work collaboratively and mentor junior