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conducting research "in the wild" (e.g., field deployments or data collection in real-world environments) Familiarity with current AI technologies (e.g., machine learning, large language models) and an
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. Describe a deep learning project you have executed, ideally a creative use of supervised fine tuning of a pre-trained vision transformer, U-Net architecture, or related topic. Projects in computer vision for
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quality monitoring, and/or nature-based water treatment designs. In addition, the candidate should have some experience in AI, machine learning, and/or managing large data sets related to water resources
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science data. For this position, we're seeking candidates with a background and expertise in Large Language Models, Computer Vision Models, Deep Neural Networks, and/or other 'AI' or Machine learning fields
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selected Master and PhD students with financial support. Where to apply Website https://www.timeshighereducation.com/unijobs/listing/408577/cbs-assistant-profe… Requirements Additional Information STATUS
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, military status, national origin, pregnancy, race, religion, sex, sexual orientation, or veteran status. Final candidates are subject to successful completion of a background check. Additional Information
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a cover letter, CV, and contact information for three references. Review of applications will continue until the position is filled. Applicants may learn more about professional development
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intelligence, machine learning, big data and network analysis, computational and Bayesian methods, are encouraged to apply. Minimum Qualifications PhD in Statistics or closely related fields with documented
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to capture the spatial complexity of tumor organization and its relationship to treatment response. This PhD project aims to develop robust multimodal predictive models of platinum resistance using a large
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part of a team, able to learn quickly, meet deadlines and demonstrate problem solving skills. Thorough knowledge of web, application and data security concepts and methods. Preferred Qualifications PhD