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Contracte Indefinit linked to the project: "Evaluation of a therapeutic strategy to shorten the length of hospital stay in pediatric complicated appendicitis: randomized, parallel, multicenter, open clinical
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current practice). Demonstrated expertise in AI/ML. Proven track record in application performance optimization. Advanced experience with parallel programming models (e.g., OpenMP, MPI, CUDA). Extensive
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field from an accredited institution. Demonstrated skills in creative problem solving and troubleshooting Experience with parallel computing and multi-core \ multi-threaded programming libraries Knowledge
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Highly organised, with the ability to remain self-motivated in keeping to project deadlines Ability to work on several tasks in parallel and to manage competing demands Knowledge of the protected
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components, integration into a wearable format, and establishing a consistent build, test, and quality-check process so that multiple units can be manufactured with comparable performance. In parallel
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the development, support, parallelization, optimization, and benchmarking of scientific applications and code using tools like Fortran, C/C++, MPI, OpenMP • Experience with and a thorough knowledge of queuing
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of memory, senescent, and exhausted T-cells with age. The PhD candidates will work on: - Identifying key metabolic pathways involved in T-cell aging using advanced genetic models that allow for parallel
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organ, on our labs own dedicated multiphoton confocal. In parallel, genomics data existing within the lab will be mined to identify candidate genes. Combining live and fixed confocal analysis, as
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imaging over multiple generations. In parallel we will build upon our new experimental and computational framework that links phenotype to function at the single-cell level (named “Look-Seq2”). Strong
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such as RNA FISH probe generation followed by imaging at the Imaging core, 3) RNA secondary structure analysis with methods such as FISH 4) RNA functional genomics with methods such as massively parallel