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meetings Potentially participate in Arctic field campaigns Be working with large data sets and developing algorithms. You should be highly motivated, self-driven, and possess strong work ethics, team spirit
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established AGATE Centre for Algorithmic Game Theory in Socioeconomics. Informal inquiries are welcome and may be sent to loebl@kam.mff.cuni.cz . Where to apply E-mail positions@kam.mff.cuni.cz Requirements
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, including artificial intelligence, machine learning, data sciences, algorithms, databases, cloud computing, software engineering, networking, operating systems and security. Job Description The successful
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computing, computer architecture, programming models and high performance computing. These are your qualifications: Must-haves: Completed doctoral/PhD studies in Computer Science or a closely related field
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foundations of feature learning in neural networks. Engage in the life of the CSD, including participating at the weekly seminars. Present results internally and at international venues; Qualifications PhD in
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deep learning algorithms. We welcome applications from individuals with experience in: Experience developing deep learning models for real-time image/video segmentation, object tracking, reinforcement
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algorithms that maximize the information extracted from images and delivered to the robot. To be successful in this role, we are looking for candidates to have the following skills and experience. We welcome
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Classification Title: Post Doctoral Associate Classification Minimum Requirements: PhD in experimental particle physics at the time of appointment. Job Description: The UF CMS group currently
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. You will take the lead on applied physics, mechanics, manufacturing processes, and algorithm/coding development within the bioprinting domain. This position is part of a larger, EU-funded Horizon Europe
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of the extraction and beneficiation system. This work will require an understanding of mining processes, mathematical modeling of flows and extraction decisions, and the use of machine learning algorithms to predict