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Field
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this short-term project we shall use active learning to accelerate the training of deep learning algorithms for optimising 2D material van der Waals (vdW) structure discovery. The goal is to make model
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atmosphere Flexible working schedule (e.g. possibility for home office, paid lunch break - depending on working hours) International training and teaching opportunities Seal of quality for in-house advancement
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in clinical trials. Regularly report on improvements or challenges. Documentation will occur via an online database 4. Support training and testing sessions: Coordinate the scheduling of training and
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. Location of Vacancy Part/Full Time Full Time Hours per Week 37.5 Work Schedule Monday – Friday 8:30 AM to 5:00 PM Must be willing to work a flexible schedule to meet the needs of the department. Type
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, design, implement, and validate an optimization system for scheduling group classes within the Koachy platform. The specific goals include: Develop attendance prediction models for different types
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either back-end Java development, front-end UI development, and/or signal processing algorithm development. This position will work on all phases of software application development ranging from
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other duties as assigned. Work Schedule 40 hours per week, worked between the time frame of Monday-Friday between the hours of 7:00 am and 7:00 pm. Flexibility is expected regarding schedules to meet
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of early pre-malignant development of ovarian carcinoma and development of early detection/screening tests/algorithms of ovarian cancer. Qualified candidates must have a Ph.D. degree in Biology, Cellular
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Artificial Intelligence, with an emphasis on developing methodologies and techniques for Evolutionary Computation and Machine Learning. Work Plan: State-of-the-art survey of Evolutionary Algorithms and Large
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, resource efficient algorithms, and programming paradigms for enabling an application-tailored design of dependable communication and computation systems. Project description This PhD project is linked