Learning support assistant Jobs in Göttingen

Job posting no. The GWDG is seeking a Storage Expert (m/f/d) to join an interdisciplinary team of HPC experts in the working group “Computing” (AG C) with a regular working week of 39 hours (100%). Remuneration is in accordance with the collective agreement for the German public service (federal government); depending on qualifications, the position will be grade TVöD E 13. The position is suitable for part-time work and initially limited till 31rd December 2029. The GWDG strives for long-term cooperation. If interested, there is the possibility of a doctorate. The Gesellschaft für wissenschaftliche Datenverarbeitung mbH Göttingen (GWDG) is the university computing center for the Georg-August-Universität Göttingen and a computing and IT competence center for the Max Planck Society. The provision of high-performance HPC systems has been one of its tasks for over 40 years. In 2020, the University of Göttingen / GWDG was accepted as one of eight computing centers in the National High-Performance Computing (NHR) network. The GWDG operates the HLRN-IV system “Emmy”, one of the most powerful computers in the world. As a national supercomputing center, the GWDG offers technical support to researchers and students from various science domains using sophisticated computer codes, including earth system science, life science, and engineering. We also participate in both national and international research projects. At the same time, we aim to improve our close collaboration with the German Aerospace Center (DLR), and specialized computing centers including the German Climate Computing Center (DKRZ) and the Institute for Advanced Simulation Jülich (IAS-JSC). As part of our AI Service Center for Sensitive and Critical Infrastructure (KISSKI) we have created a number of AI-based services that offer high levels of security and privacy due to being processed on our own hardware. The position will be located within the subproject “KISSKI-EvoKS” and closely collaborate with customers from SMEs and Startups to develop prototypes and workflows that lead to PoCs and Blueprints. Those customers will come predominantly from sectors with high data protection requirements. The GWDG together with the Faculty of Mathematics and Computer Science and the Campus Institute Data Science (CIDAS) of the University of Göttingen provides a stimulating research environment in Scientific Computing, with an opportunity to conduct research in the intersection of applied computer science, High-Performance Computing, AI, and Machine Learning. Responsibilities We have a wide range of potential responsibilities that we would like to discuss with you. Your responsibilities in our team could include, for example: Design, implement, and optimize high-performance storage solutions tailored for AI and HPC workloads Conduct research on scalable, cost-effective storage architectures suitable for AI training and HPC simulations in resource-constrained environments Develop and deploy data management strategies for large-scale AI datasets, including data lifecycle management, versioning, backup, and security (e.g., GDPR-compliant data handling) Investigate and prototype AI-optimized storage systems leveraging technologies such as NVMe, SSD caching, and distributed storage (e.g., Ceph, MinIO, Lustre) Support SMEs in evaluating and selecting appropriate HPC and AI storage solutions Collaborate with data scientists and engineers to ensure storage systems meet the demands of AI model training, inference, and real-time processing Develop best practice guidelines and toolkits for SMEs to manage AI/HPC data efficiently and security Provide technical advisory and training to SME teams on data storage, performance monitoring, and data governance Monitor and benchmark storage performance, ensuring low latency, high throughput, and cost-efficiency for AI/HPC applications Requirements Master’s degree (or equivalent) in Computer Science, Electrical Engineering, Data Science, or a related field Experience in HPC systems, storage infrastructure, and AI data engineering Proven experience with high-performance storage technologies (e.g., Lustre, GPFS, Ceph, NFS, S3-compatible storage) Strong knowledge of AI/ML data pipelines, including data ingestion, preprocessing, and model training workflows Hands-on experience with containerization (Docker, Kubernetes) and orchestration tools in HPC/AI environments Familiarity with cloud storage platforms Experience in data lifecycle management, data versioning, and metadata management Solid understanding of data security, privacy (GDPR), and compliance in AI applications Excellent analytical and problem-solving skills Excellent communication skills and ability to translate technical concepts for non-technical stakeholders Very good German skills (C1) Very good English skills (C1) Willingness to travel on business Desirable Experience in research or innovation projects related to HPC, AI, or data infrastructure Knowledge of AI-driven storage optimization (e.g., predictive data placement, auto-tiering) Familiarity with open-source HPC/AI frameworks (e.g., Slurm, Singularity, MLflow, Kubeflow) Proficiency in scripting languages (Python, Bash) and system administration (Linux/UNIX) Our offer Flexible working hours and opportunity for mobile working A modern, diverse, and exceptional work environment with close proximity to academia and research at the intersection of several innovative technology sectors An interesting, versatile job in a large, internationally operating IT competence center Collaboration in a competent and committed team Qualification and further development of your skills Social benefits of the public sector Your application Have we sparked your interest? Then please send us your application by via our online form: Website The GWDG strives for gender equity and diversity and therefore welcomes applications from any background. The GWDG strives to employ more severely disabled people. Applications from severely disabled persons are expressly encouraged. If you have any questions about the advertised position, please contact Prof. Dr. Julian Kunkel (e-mail: ). Jetzt bewerben