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Field
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, to enable scalable quantum algorithm development and quantum-HPC codesign. What is Required: PhD in Computer Science, Computational Science, Applied Mathematics, or a related field awarded within the last
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algorithms and techniques and design, implement, test, and maintain software/tools embodying those methods. You will prepare and submit grant proposals to external funding bodies. This position will also
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quantum sensing technologies (e.g., Rydberg atomic sensors) for wireless communications and sensing. Key Responsibilities: Develop quantum-related theories, models, and algorithms for various communications
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will work closely with the Principal Investigator (PI), Co-PI, and the research team to develop deep learning-based computer vision algorithms and software for object detection, classification, and
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. Prior Research Fellows have been accepted by PhD programs in computer science, economics, and political science and JD programs at top schools (e.g., Harvard, Stanford, Princeton, Yale). In recent years
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awarded to students who are enrolled in non-award courses, or up to four years, in the cases of students enrolled in a PhD. Scientific advisor: João Tiago Paulo Workplace: INESC TEC, Braga, Portugal
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available under the following conditions: OBJECTIVES | FUNCTIONS Development and evaluation of machine unlearning algorithms for speech foundation models, including: - Selection and preparation of models and
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science Mathematics Researcher Profile First Stage Researcher (R1) Positions PhD Positions Country Norway Application Deadline 22 Oct 2025 - 23:59 (Europe/Oslo) Type of Contract Temporary Job Status Full-time Hours Per
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Stig Brøndbo 22nd October 2025 Languages English English English Faculty of Science and Technology PhD Fellow in Knowledge-Driven Machine Learning Apply for this job See advertisement The position A
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include: Lead original research in multimodal and causal AI for health; design, implement, and rigorously evaluate algorithms and full pipelines. Build reproducible research pipelines and maintain reliable