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of novel methods to decompose the heterogeneity of psychiatric disorders, particularly ADHD, using large-scale genetic, imaging, and epidemiological data from Denmark and other countries. You will apply
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datasets High proficiency in data analysis and statistical programming using R and/or Python. Experience working in high-performance computing (HPC) environments for large-scale analyses and with workflow
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Background in machine learning or deep learning methods, including Graph Neural Network (GNN) Experience with Large Language Models (LLMs) applied to biological data collection, extraction, and standardization
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are software representations of physical assets, processes, or systems. They leverage real-time data to mirror the behaviour and characteristics of their physical counterparts, enabling predictive maintenance
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Do you enjoy finding solutions to integrate and analyse large data sets of biodiversity dynamics and their drivers? Are you creative and able to couple various data flows and integrated modelling
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candidate is expected to work closely with Professor Rubina Raja, on several tasks, including: Supporting large research/publication projects (including copyediting and indexing) Carrying out data collection
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We are offering a PhD fellowship in biomolecular (single molecule) native mass spectrometry commencing 1 January 2027 or shortly thereafter. Our group and research Proteins and other large
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developing new techniques for analyzing security of open-source components and large-scale applications. Applicants are expected to have a strong background in Programming Languages and Software Engineering
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to investigate the storage and resource potential within sedimentary basins in the Kingdom of Denmark. GEUS further collects large amounts of marine and onshore seismic data to improve our understanding
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. Desirable qualifications include: • Experience with large epidemiological data and infectious diseases is highly beneficial. • Prior exposure to virological laboratory techniques and/or epidemiological data