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The Translational Cancer Immunogenomics (TCI) Research Group, led by Dr. Ángel Álvarez-Prado at the Department of Cancer Research of LIH, is currently offering a Ph.D. student position. Recently established, the research group focuses on understanding how genetic alterations in cancer cells...
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apply a fast and efficient forest trait mapping and monitoring method based on the Invertible Forest Reflectance Model. A machine learning / deep learning framework will be explored and developed
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contact details · List of publications (and patents, if applicable) · Contact details of 2 references Please apply ONLINE formally through the HR system. Applications by email will not be
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training unit: https://www.list.lu/en/research/project/forfus Do you want to know more about LIST? Check our website: https://www.list.lu/ How will you contribute? Your PhD work will focus on outdoor forest
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machine learning methods to investigate how ecosystem water stress and drought disturbances affect relevant forest ecosystem functioning at various scales. It will enable advanced assessment of forest
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susceptible to SM, VWC, and atmospheric delay. As a result, the objective of this PhD project is to develop models able to fuse backscattering and phase information to estimate SM and VWC more accurately. The
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LLM-based vulnerability detection systems. Robustness evaluation framework: you will develop comprehensive assessment methodologies to quantify the weaknesses and limitations of LLMs in software
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· PhD in Aerospace Engineering, Mechanical Engineering, Applied Physics, or a closely related discipline. · Strong academic background in computational mechanics, fluid dynamics, electromagnetics
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into this material and support tailoring its properties. For this, you will: Contribute to method development for ultra-fast MLIPs (Xie et al., npj Comput. Mater., 2023) Develop realistic MD simulation protocols
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Your profile described below? Are you our future colleague? Apply now! Education You hold a PhD degree with demonstrated theoretical and practical knowledge in Materials science, Materials chemistry and