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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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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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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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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
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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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statistical evaluation Machine learning analyses: implementation of established and new workflows Coordination of activities with Consortium partners, including presentation of results at consortium meetings