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modeling, machine learning, and AI techniques applied to biomedical data is a plus. Clinical Proteomics: Experience with clinical trial data, real-world evidence (RWE), and biomarker-driven trial designs is
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combining two of Europe's new satellite sensors. If you have interests in physics, climate and machine learning, this is the Doctoral student position for you! About us Our team is part of the Division
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different backgrounds. This position requires that you have graduated at Master’s level in in computer science, media technology, computer engineering, human-computer interaction, visual learning and
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from talented and highly motivated candidates to pursue a PhD in machine learning at KTH, Sweden, and NTU, Singapore. This is a fully funded, joint doctoral position that will lead to a joint PhD degree
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well as the programmes in statistics, cognitive science and innovative programming. Read more at https://liu.se/ida The position is based at the Division of Statistics and Machine Learning (STIMA). We conduct research
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degree in machine learning. The successful candidate will be supervised by professor Aristides Gionis (https://www.kth.se/profile/argioni/ ). The research team focuses on developing novel methods
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at: https://www.umu.se/en/department-of-computing-science/ Project description and working tasks The project will develop privacy-aware machine learning (ML) models. We are interested in data driven models
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of 20 per cent of full-time. Your qualifications You have a master’s degree in electrical engineering, engineering physics, mechanical engineering, computer engineering, engineering mathematics or have
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contribute to exciting research in theory of machine learning, in a collaborative and dynamic environment. In the rapidly growing area of artificial intelligence (AI), this position is a uniqure chance to
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through a model-driven approach, i.e. a combination of simulation- and data-driven methods and tools with data analysis and machine learning as an important part. The work builds on established theories and