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Field
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analysis, statistical modelling, linear mixed models, and machine learning among others. The position is well suited for an individual interested in quantitative genetics and data analysis that wishes
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-edge high-performance computing (HPC) that incorporate machine learning/artificial intelligence (ML/AI) techniques into visualizations, enhancing the efficiency and reliability of scientific discovery
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machines into the cellular context in space and time, how stress factors influence these processes, and how the cellular network enables their robust functioning. Research Focus 3 Microbes providing
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and machine learning with Prof. Jason M. Klusowski (https://klusowski.princeton.edu). The position is for one year with the possibility of reappointment based on satisfactory performance and
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grant when extending an offer. PhD in neuroscience or in related field. Please include C.V. and cover letter. For people in the EU, click here for information on your privacy rights under GDPR
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statistical evaluation Machine learning analyses: implementation of established and new workflows Coordination of activities with Consortium partners, including presentation of results at consortium meetings
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researchers in applied mathematics and machine learning. This is due to its remarkable flexibility, mathematical elegance, and as it has produced state-of-the-art results in many applications. As a leading
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expected to be fully in person. This position does not have any supervisory responsibilities. Qualifications include a PhD in psychology or a related field and previous experience working in a research
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or junior graduate students. A formal training, education, or certification in a secondary area (beyond the main PhD focus) such as additive manufacturing, advanced/hybrid manufacturing, machine learning
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Job Description Do you want to do research on cutting-edge machine learning methods? If you are building a career as a researcher in machine learning and are passionate about working with cutting