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interpreting large datasets using statistical programming languages (e.g. R, Python etc.) Proven independent working style, technical problem solving, data analysis and generation of novel ideas Proficient
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QGG - Aarhus University seeks a postdoc researcher in sustainable breeding: developing simulation...
or Population Genetics. Proficient in R and Python programming is essential. Familiar with breeding programs and breeding goals. A collaborative colleague and a good communicator. Experience in collaborating with
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robotics, drones, UAVs, multi-robot systems or smiliar, and practical applications of LLMs, agents, RAG, MCP, or fine-tuning. Proficiency in software development (Python, C/C++), skills in data analysis, and
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Postdoctoral Researcher in Natural Language Processing and Digital Humanities (18 months, full-time)
: Prepare, clean, and structure multilingual textual corpora (Greek and Latin) Develop and customize NLP pipelines in Python (including model adaptation for humanistic Latin) Implement and evaluate word
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should possess experience in robotics, drones, UAVs, multi-robot systems or smiliar, and practical applications of LLMs, agents, RAG, MCP, or fine-tuning. Proficiency in software development (Python, C/C
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, genetics and physiology Experience with bioinformatics and coding in Python or other programing language Experience with protein software tools like AlphaFold3, Boltz2, PyMOL, Chimera, etc. Interest in
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optimization is considered a strong advantage. Experience with Python scripting for data analysis is considered valuable. A strong commitment to research. Enthusiasm for working with research students
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motivated scientist with strong expertise in protein molecular modelling, protein science, biochemistry and programming in Python and usage of SnakeMake. The applicant should also have experience in working
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for predictivemodelling and large foundation models for earth systems. Skillsetssuch as programming in Python/R, Google Earth Engine, JavaScript, database management environments, Geographical AI, and machine learning
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Experience with scientific programming (e.g. in python) Experience with modelling of disordered materials is seen as an advantage Experience with automated computational workflows is seen as an advantage