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Field
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models Applying imaging modalities to support drug distribution and efficacy studies Collaborating with national partners across a multidisciplinary research network This position offers a unique
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, the impact of blowing snow on local and regional scales. The PhD candidate will produce mass balance simulations that support estimates of snow distribution for biodiversity and ecosystem assessments, as
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GPU acceleration, cloud computing, and distributed architectures, to enable efficient analysis of large-scale video datasets. Collaborate with clinical and academic collaborators, external partners
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of images of galaxies with photometric redshifts that can be used to extract the gravitational lensing effect caused by the distribution of dark matter in our Universe. The successful candidate will be
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cloud platforms for compute and storage. Version Control & CI/CD: Git, automated testing, deployment workflows. Experience with Linux systems, HPC, and distributed computing environments. Knowledge
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that are internationally leading. The faculty has approximately 3,000 students and around 500 employees, distributed across the faculty administration and six departments: the Department of Electrical Engineering and
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years. The nominal length of the PhD programme is three years. The fourth year is distributed as 25 % each year and will consist of teaching and other duties. The objective of the position is to complete
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, nonverbal behavior, affective features, facial expressions, movement, and other sensor data. Experience with multi-GPU training, distributed computing, and efficient experiment management is important for
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explore machine learning techniques and adversarial approaches to assess vulnerabilities and propose adaptive defense mechanisms, with the aim of strengthening resilience and security in these distributed
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Fundos and FCT, is now available under the following conditions: OBJECTIVES | FUNCTIONS The goal of this work is to develop a geo-distributed transactional storage based on shared logs design. The student