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Field
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profiles. Identification of molecular signatures in platelet disorders and bleeding disorders of unknown cause (BDUC). Development of machine learning models for patient stratification. Integration
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language processing, large language models, machine learning, network analysis, social media analytics, and large-scale analysis of online discourse and communities. This PhD scholarship will be based within
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, scientific rigor, analytical thinking, and the ability to work independently and collaboratively are essential. Required License/Registration/Certification N/A Physical Requirements Work in the laboratory may
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: fluctuating renewable energy, dynamic electricity prices, and increasing system complexity. In the future, industrial energy systems will not simply run. They will understand themselves. They will learn from
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imaging. Experience with scientific programming (e.g., MATLAB, Python and/or C++). Excellent analytical and problem-solving skills. Interest in image reconstruction, beamforming, machine learning, and
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, scientific rigor, analytical thinking, and the ability to work independently and collaboratively are essential. Required License/Registration/Certification N/A Physical Requirements Work in the laboratory may
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Research Center Borstel - Leibniz Lung Center | Hamburg Gro Borstel, Hamburg | Germany | 2 months ago
Bioinformatics or in Computer Science, Data Science, Statistics, etc. with focus on molecular biology • Strong quantitative and analytical skills, with a keen interest in microbial genomics and host-pathogen
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combining analytical and numerical approaches to model realistic quantum experiments and appreciate how the two complement one another. You are eager to learn new techniques and explore unfamiliar ideas
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analytics. This PhD project focuses on methods development to support pharmacovigilance using real-world data (RWD). You will define, implement, benchmark, and validate workflows for reliable detection and
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experimental laboratory skills with an interest in working alongside advanced computational and analytical technologies. Experience in interdisciplinary research and collaborative science is highly desirable