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Scientific Team Leader, Researcher (f/m/d) Deep Learning / AI

Veröffentlicht am 31. Oktober 2019 (vor 42 Tagen)
Bewerbungsende 31. Januar 2020 (in 50 Tagen)
Forschungszentrum Jülich GmbH Jülich
As a member of the Helmholtz Association, Forschungszentrum Jülich makes an effective contribution to solving major challenges facing society in the fields of information, energy, and bioeconomy. It focuses on varied tasks in the area of research management and utilizes large, often unique, scientific infrastructure. Come and work with around 6,100 colleagues across a range of topics and disciplines at one of Europe's largest research centres.

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, situated within Research Center Jülich (FZJ), member of Helmholtz Association.

To advance large-scale machine / deep learning (ML/DL) research with High Performance Computing (HPC), JSC sets up a High Level Support Team (HLST). Focused on software development and research support for ML/DL, HLST will become part of the recently launched Helmholtz Artificial Intelligence Cooperation Unit (HAICU). HAICU is a Helmholtz-wide platform consisting of 6 Helmholtz Research Centers across Germany, FZJ being among them. HAICU aims to reach an international leadership position in basic and applied AI research by combining advanced methods from ML/DL with Helmholtz' unique scientific questions and data sets - bringing together scientists from all Helmholtz centers, scientific partner institutions and industrial partners and fostering open, transdisciplinary research, with strong dedication to principles of open science and open source. At JSC, HLST will work on setting up HAICU close together with the research-oriented Cross-Sectional Team Deep Learning (CST-DL). The research topics will include large-scale, self-supervised, multi-task continual learning for growing general AI models on modular supercomputers, physics-informed Deep Learning, transfer and few-shot learning for cross-domain applications. Special focus will be on making use of highly scalable and distributed ML/DL methods on HPC facilities hosted at JSC.

We are looking to recruit a member of HLST

Scientific Team Leader, Researcher Deep Learning / AI

Your job:
  • 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 Machine Learning / Deep Learning (ML/DL) and related methods with focus on large-scale HPC applications
  • work close together with Cross-Sectional Team Deep Learning based at JSC 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
  • provide and coordinate support to HAICU research community for their scientific projects that involve ML/DL technologies and tools, including symposia, workshops, lectures, tutorials and hackathon organization
  • conduct your own research, acquire new research projects and funding, publish and present findings and research outcomes of your own research and of the projects supported by HLST
Your Profile:
  • 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 (e.g. support tickets, documentation, quality control, etc.)
  • 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
  • experience with High Performance Computing (ideally ML/DL related, CPU and GPU-based)
  • very good knowledge of English in written or spoken form
  • ability to present your work at international conferences
Our Offer:
  • 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 for a substantial fraction of your working time
  • outstanding research and computing infrastructures in one of Europe's largest supercomputing facilities
  • a comprehensive further training program
  • flexible working hours and various opportunities to reconcile work and private life
  • limited for 2 years with clear possible longer-term prospects (long-term HAICU funding already set and confirmed)
  • full-time position with the option of slightly reduced working hours
  • salary and social benefits in conformity with the provisions of the Collective Agreement for the Civil Service (100 % TvöD, Level 13-14, depending on prior experience)
Forschungszentrum Jülich aims to employ more women in this area and therefore particularly welcomes applications from women.


We also welcome applications from disabled persons.

We look forward to receiving your application until 31.01.2020 via our online recruitment system.


Questions about the vacancy?
Contact us by mentioning the
reference number 2019-254: career@fz-juelich.de
Please note that for technical reasons we cannot accept applications via email.

www.fz-juelich.de
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