2 of 2 Distributed Computing Jobs in the Thames Valley

challenges and advance biology engineering. EIT fosters a culture of collaboration, innovation, and resilience, valuing diverse expertise to drive sustainable solutions to humanity's enduring challenges. The High-Performance Computing (HPC) Engineer within GBI will play a pivotal role in designing, building, and maintaining advanced computational infrastructure to accelerate biological and biomedical discovery and translational research. Working within the … Scientific Computing Facility, the HPC Engineer will design, deploy, and optimise systems that enable large-scale data processing, AI-driven analytics, and simulation workloads across. For example deploying Kubernetes and Slurm to enable real-time data analysis from instruments, MLOps, or scientific workflow managers. We will be hiring either at the regular or senior level, depending on the applicant … position requires technical expertise in HPC system architecture, coupled with the ability to collaborate closely with data scientists, bioinformaticians, and software engineers to ensure seamless, high-performance access to computing resources that support GBI's research mission. At the senior level: This position requires deep technical expertise in HPC system architecture, coupled a proven track record to collaborate closely More ❯

implementation decisions. â Embrace Agile/Scrum methodologies, delivering and demonstrating working solutions at the end of each sprint â Stay current with emerging technologies and trends in geophysical computing and software development. Required Education and Skills â BS or MS degree in computer science, Geoscience, Applied Mathematics, or a related engineering discipline. â Minimum of 10 years of … â Knowledge with geoscience software tools and formats: o SEG-Y, Landmark seismic BRICK, CMP, OpenVDS o DSG, Petrel, Kingdom, GeoFrame, or PaleoScan â Familiarity with cloud platforms and distributed computing: o Restful API design and implementation o AWS and Azure o Tools for scalable data processing: Kubernetes, Spark â Experience with Java 2D graphics and 3D OpenGL … programming. â Experience with scientific computing libraries and frameworks: o Python: NumPy, SciPy, Pandas, TensorFlow (for ML/AI) o C Java: CUDA (for GPU acceleration) o Angular or React o Microservice: Quarkus, Spring Boot, AWS API Gateway o Docker, Kubernetes With over 90 years' combined experience, NES Fircroft (NES) is proud to be the world's leading engineering More ❯