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Field
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provides professional education nationally and internationally, supporting lifelong learning. M2 strives for close collaboration between academia, industry, and society, focusing strongly on practical
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, including artificial intelligence, machine learning, data sciences, algorithms, databases, cloud computing, software engineering, networking, operating systems and security. Job Description We are seeking
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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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or a closely related field (PhD candidates who have submitted or are about to submit their thesis will be considered) Experience of machine learning frameworks (e.g. TensorFlow) Knowledge of Python and C
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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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of data at high luminosity (after Upgrade-2), participation in coordination of activities in software groups or data analysis groups, coaching of PhD as an auxiliary supervisor on machiner learning, new
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Qualifications PhD in Robotics, Electrical & Computer Engineering, Mechanical Engineering, Biomedical Engineering, Computer Science, or closely related field. Must have PhD conferred upon hire. Preferred
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control venues such as the IEEE Conference on Decision and Control and IEEE Control Systems Letters, and in top machine learning conferences such as NeurIPS, ICML or AAAI, is expected. Proficiency in MATLAB
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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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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