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engineering Engineering » Thermal engineering Researcher Profile Established Researcher (R3) Positions PhD Positions Application Deadline 10 May 2026 - 23:59 (Europe/Brussels) Country Poland Type of Contract
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the undergraduate and graduate levels. Where to apply Website https://www.bth.se/english/vacancies/job/phd-student-position-in-software-engin… Requirements Research FieldComputer science » Computer systemsEducation
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Post-Doctoral Associate in the Center for Interdisciplinary Data Science and Artificial Intelligence
, leveraging on data analytics and machine learning to improve learning outcomes and engagement in the classroom, and Development of personal GPT-powered AI tutors that use the knowledge from (1) to provide
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& Solar Power Plants Battery Energy Storage Systems (BESS) Smart Grids & Power Systems Sustainable buildings, communities and cities[EC1.1] Artificial Intelligence & Machine Learning for Energy Digital
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(SHORES) and the Division of Engineering, New York University Abu Dhabi, seek to recruit a Postdoctoral Associate to work on a fascinating project focused on the development machine-learning powered digital
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provide the possibility for the student to work with LLMs and machine learning. Your competencies Interest in learner centered technology design, in particular how AI systems can scaffold reflection, agency
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/deploying deep learning models and machine learning applications. Computer skills: Python (PyTorch, TensorFlow), databases (MySQL), 3D Slicer, ITK-SNAP, OpenCarp. Previous experience in research activity in
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are essential Additional qualifications Experience and courses in one or more subjects are valued: statistical machine learning, optimization, deep learning and signal processing. Rules governing PhD students
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Classification Title: Lecturer/Sr Lecturer/Master Lecturer Classification Minimum Requirements: PhD in engineering or a closely related discipline Job Description: The Department of Engineering
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on tungsten samples and candidate tungsten alloys will validate the simulations and guide the design of more dust-resistant materials. Finally, we will use machine learning to integrate simulation and