The Jülich Supercomputing Centre (JSC) is a research institute that operates one of the most powerful supercomputer infrastructures for scientific and engineering applications in Europe.
Scientific Team Leader, Researcher Deep Learning / AI
Forschungszentrum Jülich -
Forschung & Entwicklung
• lead a cutting edge High Level Support Team (HLST) that as a part of HAICU unit will host 4 Deep Learning/AI System and Software Engineers
• define and coordinate research, open source software development and research support activities for ML/DL and related methods with focus on large-scale HPC applications
• work close together with other teams to define and push forward common long-term research goals and long-term open software libraries, platforms and data services with high usability and impact across domains and ML/DL community
• establish tight connections with HAICU Centers, other HLST Teams across the Helmholtz centers and HAICU local partners to build up open research community
• excellent Master or Doctorate (preferred) degree in computer science, machine learning, mathematics, physics or a related subject
• ability and ideally experience to lead a small team of experts with heterogeneous skills, to organize and coordinate group tasks
• research experience in ML/DL field, documented in your dissertation, peer-reviewed publications, project experience, participation in top conferences (NeurIPS, ICLR, ICML, etc.)
• practical experience with ML/DL toolchains and workflows documented in your dissertation, peer-reviewed publications, or project experience
• advanced experience with high level programming languages (C++, Python) and best software engineering practices
• work on frontiers of scientific and technological challenges as team leader with access to cutting-edge and unique supercomputing systems
• Develop your academic career and engage in the supervision of master and doctoral students in the highly diverse fields.
• If desired, option towards obtaining a PhD degree can be offered in frame of Helmholtz School for Data Science in Life, Earth and Energy (HDS-LEE) that provides an interdisciplinary environment for educating the next generation of data scientists in close contact to domain-specific knowledge and research. Application to HDS-LEE is possible after PhD topic is defined.
• freedom to work on your own research questions
Dauer: 2 years
Vergütung: 100% TvöD, Level 13-14
Anzahl der Plätze: 1
Angaben zum Unternehmen
Forschung und Entwicklung im Bereich Ingenieurwissenschaften