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to enable quantitative, high-resolution, time-lapse monitoring of soil properties and will be implemented using high-performance parallel computing. This PhD position offers the opportunity to work at the
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also include trouble shooting capabilities. Desirable skills include working knowledge of Linux, FORTRAN, Python and C++; experience with machine learning, parallel computing and high-performance
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health. Conduct a human intervention study to assess the efficacy of a very long chain polyunsaturated fatty acid supplement on signs and symptoms of dry eye. Methods to be used: A parallel randomized
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to be used: A parallel randomized controlled human intervention study will be conducted in adults (18-65 yrs). Participants will be randomly allocated to one of three intervention groups: (I) Omega-3
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computing software libraries (e.g., Trilinos, MFEM, PETSc, MOOSE). Experience with shared and distributed memory parallel programming models such as OpenMP and MPI. Experience with one more GPU or performance
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Science, Computer Engineering, or a related field, completed before the fellowship start date. Candidates should demonstrate experience in at least two of the following areas: compilers, parallel programming
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using a weighted tube receptor). In addition, samples will be collected from water points and micro-watersheds in Itatinga close to the EucFlux site during the second phase of the project. In parallel
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– Documented experience in large-scale data management, high-performance computing systems, GPU acceleration, and parallel file systems – Ability to communicate fluently in English, both spoken and written
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, and execution of unit, system, integration, parallel, and performance testing using AI-assisted tools where applicable. Identifies opportunities to embed AI capabilities into applications, such as
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of behavioral responses, particularly pain-related outcomes, alongside detailed analysis of tissue inflammation and degeneration. In parallel, cellular studies using human primary cells will provide mechanistic