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is expected to generate novel analytical methodologies, peer-reviewed publications, conference presentations, and practical tools for forensic laboratories. During the PhD project, you will design and
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data sources (e.g., registry data, surveys, and organisations). Your competencies Digital methods such as machine learning based classification, computational text analysis, network analysis, web
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industrial energy systems that combine physics and data to become adaptive, autonomous and trustworthy? To get there, you will work at the intersection of thermal energy systems, machine learning and
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machines Conduct simulations and experimental testing to validate system performance Document and disseminate research results through scientific publications and presentations The PhD candidate will work
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, cryo-electron microscopy (cryo-EM), cryo-EM-based polyclonal serology (cryo-EMPEM), molecular dynamics simulations, machine learning, and structural biology to define epitopes and engineer improved
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electrical engineering, control engineering, applied mathematics, computer science, or a related field A strong background in probability and statistics, machine learning, or control theory Interest in cyber
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. linguistic bias), specifically the effects of grammatically un/gendered languages and the masculine default, on gendered representations using corpus linguistic methods; reveal how AI tools echo and reinforce