Hpc Engineer Traineeship (Erasmus Candidates Only)

HPC Engineer Traineeship (Erasmus Candidates Only)Engineering and / or Technology, Mathematics and / or Informatics, Natural Sciences This is a Digital Opportunities Traineeship (DOT). If you want to apply for this internship, please remember that you have to be a student or recently graduated based in one of the 33 Programme Countries participating in Erasmus or the Horizon 2020 Associated Countries. Before applying for a Digital Opportunity Traineeship, we encourage you to check with your university if you are eligible for Erasmus traineeship. You can read more about DOTs on our information page. General information Duration : 5 – 6 months Commitment : Full-time, 35 h / week (10 : 00 – 17 : 00) Location : Via Casilina 3T, Rome, Italy Mode : On-site / partial remote work / full smart working Description We offer a technical traineeship in High-Performance Computing for the BIO-DRIVEN system, a multi-layer platform that models and optimises biological ecosystems. The trainee will shape HPC workflows, benchmark and tune CPU / GPU jobs, and automate deployment to ensure models run efficiently from development to production. Qualifications Enrolled in or recently graduated from a Master’s programme in Computer Science, Computational Engineering, Physics, Data Science, or a related field. Technical Skills Write clean code in Python and C / C++ or Fortran. Use MPI, OpenMP, or CUDA for parallel or GPU programming. Operate job schedulers such as SLURM and container tools like Docker or Singularity. Work comfortably in Linux, Git, and basic CI / CD. Apply profiling and optimisation techniques to HPC workloads. Learning & Development Show strong interest in scaling AI / ML workloads from laptop to cluster. Solve low-level issues independently and document findings clearly. Collaboration & Communication Present benchmark results and optimisation recommendations to data scientists and project managers. Coordinate with infrastructure and application teams to embed HPC best practices into the BIO-DRIVEN stack. Daily Tasks Benchmark and profile training and inference jobs on CPU / GPU nodes. Implement optimisations such as mixed precision and communication overlap. Automate job submission, monitoring, and reporting through scripts and CI pipelines. Package models and dependencies into portable containers for cross-environment deployment. Maintain run-books that capture optimisations, test cases, and troubleshooting steps. How to Apply Submit your CV and Cover Letter, indicating your preferred internship period. Name the file accordingly. J-18808-Ljbffr J-18808-Ljbffr

Location: Veneto, IT

Posted Date: 8/20/2025