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Field
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of very large data sets, data analysis, and simulations of X-ray scattering and spectroscopy signatures of dynamic processes in battery materials. The theoretical/ simulation efforts are supported by
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. Qualifications Applicants with experience in mixed methods, particularly digital methods, data scraping/analysis and qualitative research (Netnography and interviews) will be preferred. Proficiency in English and
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and technicians to solve analytical challenges and develop, optimize, validate and apply analytical methods to evaluate food safety. Key Responsibilities - Perform trace-level analysis of organic
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and reduction of very large data sets, data analysis, and simulations of X-ray scattering and spectroscopy signatures of dynamic processes in battery materials. The theoretical/ simulation efforts
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. The ideal candidate will demonstrate: Proven experience in thermodynamic modelling, thermo-economic analysis, and multi-objective optimization. Strong publication record in thermal conversion systems (e.g
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expertise in thermo-fluid engineering, thermodynamic modelling, and optimization. The ideal candidate will demonstrate: Proven experience in thermodynamic modelling, thermo-economic analysis, and multi
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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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in the communication, analysis and execution of processes. You will be part of a team at DTU Computed supported by the Villum Synergy Fund and through the Danish Interdisciplinary Center for Digital
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academic qualifications at the PhD level in bioinformatics, computational biology, biomedical sciences or a related field. Documented expertise in scRNA-seq analysis and familiarity with spatial
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international quality, including publication. Single cell RNA sequencing and data analysis Characterization and production of monoclonal antibodies Flow cytometry Confocal microscopy qPCR In vitro cell cultures