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discipline. Strong experience in numerical/computational modelling (e.g., FEM/multiphysics, wave propagation, computational mechanics). Evidence of scientific programming and good software/reproducibility
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management requirements, such as data planning, collection, processing and compliance, pertaining to the Faculty of Medicine data platforms, software, and tools in support of good data management practices
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software such as STATA, R, or Python. Potential to publish articles in high quality international academic journals. Ability to work in teams as well as independently. Written and spoken proficiency in
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projects to be developed in the same context. Opportunity to develop software in a real-world environment, working within a professional team and contributing to systems used daily by thousands of users
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. The ability to obtain source code access to export controlled nuclear software, including VERA. Preferred Qualifications The ideal candidate will have experience in methods and software development related
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, or embedded software tools. Integrate controller logic with the microgrid model and validate performance under different simulated conditions. Conduct testing of control strategies under various operating
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and open-source release of training and evaluation pipelines. The selected candidate will be integrated into a research team with established expertise in software security, program analysis, and AI
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software scaffolding to support early deployment, and providing hands-on technical support to the animal research lab during in vivo testing. Responsibilities* Responsibilities also include coordinating day
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conferences/journals, such as CVPR, ICCV, ECCV, NeurIPS, ICLR, ICML, etc.; Knowledge of scientific or engineering software like PyTorch, TensorFlow, etc.; Demonstrate outstanding communication skills, clear
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analyses. Design, maintain, and optimize computational pipelines and software tools for integration of multi‑omics and clinical datasets to uncover mechanisms of tumor evolution and therapeutic resistance