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To be eligible for this award, students must: be currently enrolled in a PhD at Flinders University; have secured an internship agreement in writing, for an eligible internship within the first 18
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automated vehicles, the design of control center and teleoperation concepts, and sustainable mobility and operational concepts in public transportation. A particular focus is on the technical supervision
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, finance or computing science/natural language processing/machine learning. Preference will be given to those who are proficient in Python, adept at processing large-scale data and have worked with large
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dives into data from online consumer feedback and the embedded environmental footprints of each stem. This project will focus on the interface between the product’s aesthetic and data-augmented generative
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Kingdom. The Studentship is named in honour of the late Professor S.F.C. Milsom, sometime Literary Director and President of the Society. The studentship is tenable for a maximum of three years, subject to an annual review
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of typically 250 kHz and 2.7 V/cm. The commercial electric field system is usually supplemented with chemotherapy drugs. Pancreatic cancer patients only have a 10%, 5-year, survival rate. Little electric field
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) to work on the development of an Amazonian Early Warning System (AmEWS) integrating Earth Observation data, process-based ecosystem models, and advanced machine learning approaches. The position is embedded
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monitoring Apply for this job See advertisement This is NTNU NTNU is a broad-based university with a technical-scientific profile and a focus in professional education. The university is located in three
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13.03.2026, Academic staff A fully funded PhD position (initially 75% TV-L E13, increasing to 100% TV-L E13 after 8 months) is available at the Professorship of Optimization and Sustainable Decision
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transformer lifetime, and improved security of electricity supply. This PhD position is part of the larger research project KSP ClampIT – Clamping forces in Transformers: Online monitoring and predictive