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off-the-shelf sensors and the development of resilient algorithms that combine first-principles modeling with modern machine learning techniques. The goal is to push the boundaries of robust perception
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on causal and mechanistic studies of microbiome-mediated pathogenesis. This is achieved by bridging microbiology and big data analytics in a structured doctoral training environment. The need of microbiome
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are looking for a highly motivated and skilled PhD researcher to work on structural surrogates of offshore wind foundations through graph-based machine learning. Our goal is to perform full-structure
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of Unix systems (GNU Linux) and keen to gain hands-on experience in Networks and systems Machine Learning knowledge is a plus Strong analytical and programming skills are required (Python, Matlab, Golang
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problems in biology by combining machine learning with in-depth knowledge of biological processes. Who we are looking for You have a Master in Science (Bioengineering, Biochemistry-Biotechnology, Biomedical
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interest to acquire those in exercise physiology, metabolic & inflammatory regulation, molecular biology and biochemistry. Experience with basic molecular biology techniques, such as protein/mRNA extraction
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, Natural Sciences or related disciplines be very motivated and enthusiastic to learn and expand both computational and experimental skill set have an analytical mindset be able to summarize data extracted
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MSc in Systems Biology, Molecular Biology, Natural Sciences or related disciplines be very motivated and enthusiastic to learn and expand both computational and experimental skill set have analytical
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with causal inference or debiased machine learning is a plus. - You are creative and have strong analytical skills. - You are a team player, motivated to work in a team of statisticians, and have strong
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strong analytical skills to interpret the obtained experimental results. You are driven to do independent research, and you have a strong self-learning ability. A creative and inquisitive attitude is a