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[Malaysia Campus- VPSSP] An AI-Informed Planetary Health Framework for Equitable AMR Risk Mitigation
from Project 1, we will conduct focus groups and interviews with communities in high- and low-risk zones to capture local knowledge, behaviours, and risk perceptions related to AMR. In parallel, key
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of running at scale within high-performance computing (HPC) environments. In parallel, the postholder will undertake the bioinformatic analysis of NGS datasets, generating the data and insights required
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/Qualifications Technical Skills: Processing and analysis of large volumes of data from numerical simulations. Parallel programming standards in distributed memory (MPI) and shared memory (OpenMP). HPC
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is BTH's largest department, with just over 70 employees. The department conducts research in computer science, covering the subfields of big data and AI, parallel computer systems, visual and
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scalable training and inference on parallel, distributed and GPU-accelerated computing systems Benchmark the developed approaches against established methods, assessing predictive performance, generalisation
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of interaction, covering linear, parallel, multithreaded, branched and non-linear narrative structures, and the balance between interactivity and narration within a project. Students examine nonlinear digital
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are looking for candidates with extensive experience in HPC architecture, cluster management, and parallel computing, with a proven ability to work within highly secure and regulated environments
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are required. Experience in python, Fortran, C++ and parallel computing are a plus. 3. Good publication record in peer-reviewed journals for fluid mechanics. 4. A Ph.D. degree in relevant
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security guarantees. In parallel, we will investigate how modern AI techniques can accelerate large-scale formal verification, developing AI proof agents that can maintain, extend and refactor the seL4 proof
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to candidates having a strong record in developing novel computational strategies to solve complex physics problems with relevant experience in nonlinear analysis of pdes and parallel computation. FLSA Exempt