Scientific Team Leader, Researcher Deep Learning / AI
Forschungszentrum Jülich

Title Scientific Team Leader, Researcher Deep Learning / AI
Employer Forschungszentrum Jülich
Job location Wilhelm-Johnen-Straße, 52428 Jülich
Published August 9, 2019
Application deadline September 1, 2019
Job types Researcher
Fields Algorithms, Artificial Intelligence, Artificial Neural Network, Computer Communications (Networks), Computing in Social science, Arts and Humanities, Human-computer Interaction, Operating Systems, Programming Languages, Software Engineering and 1 more.


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) at Forschungszentrum Jülich operates one of the most powerful supercomputer infrastructures for scientific and engineering applications in Europe and grants scientists in Germany and Europe access to the supercomputing resources for their research.
JSC sets up a High Level Support Team (HLST) as part of the recently launched Helmholtz Artificial Intelligence Cooperation Unit (HAICU). HAICU is a Helmholtz-wide platform that aims to reach an international leadership position in basic and applied AI by combining advanced methods from Machine Learning (ML) and Deep Learning (DL) with Helmholtz' unique research questions and data sets - bringing together scientists from all Helmholtz centers, other partner institutions and fostering open, transdisciplinary research. Specific HAICU topics at JSC carried out together with Cross-Sectional Team Deep Learning will be continual learning, scalable and distributed ML and DL in extreme-scale computing, physics-informed Deep Learning and transfer learning for cross-domain applications.


We are looking to recruit a

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, software development and support activities on Machine Learning / Deep Learning (ML/DL) 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 research goals and long-term open software platforms with high usability and impact across domains and Machine Learning / Deep Learning community
establish tight connections with the HAICU Central, other HLS-Teams across the Helmholtz centers and HAICU local partners to build up an open community of HAICU researchers
stay abreast of current trends and best practices in configuration of ML/DL tools on HPC Systems
discuss with HAICU users how the support services can be improved and perform requirement evaluation / assessment from scientific users in order to understand which tools and technologies are required to provide optimal support and ML / AI tool development
assist in the HLST coordination and acquisition of new research projects subject to your abilities and interests
publish findings and research outcomes of your own research and/or together with members of research communities that take advantage of the HLST activities

Your Profile:

Master's or Doctorate degree (preferred) from a university with internationally accepted quality standards in computer science, software engineering, data science, machine learning, mathematics, physics or a related subject
ability and ideally experience to lead a small team of experts with heterogeneous skills, to follow-up and follow-through of group tasks (e.g. support tickets, documentation quality control, etc.), to resolve team conflicts, and be able to prioritize 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 (e.g. TensorFlow, pyTorch, mxNet, Chainer, Keras, Horovod, etc.) documented in your dissertation, peer-reviewed publications, or project experience
advanced experience with high level programming languages (C++, Python)
experience with High Performance Computing (HPC, also GPU-based) and corresponding workflows and toolchains (Slurm, MPI, CUDA, etc.)
very good knowledge of English in written or spoken form
ability to present your work at workshops and international conferences

Our Offer:

opportunity to work on interesting challenges as team leader and research questions with access to cutting-edge and unique HPC systems
possibility to develop your academic career and engage in the supervision of master and doctoral students in the fields of software engineering, machine learning and computer science; if desired, option towards obtaining a PhD degree can be provided
freedom to work on your own research questions for a predefined fraction of your working time
excellent research and computing infrastructures in one of Europe's largest research facilities
a comprehensive further training programme
flexible working hours and various opportunities to reconcile work and private life
limited for 2 years with possible longer-term prospects (already funding-wise 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 (TVöD)
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, preferably via our online recruitment system on our career site until 01.09.2019, quoting the reference number 2019-254.

Questions about the vacancy?
Contact us by mentioning the reference
number 2019-254:
Please note that for technical reasons
we cannot accept applications via


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