Scientific Team Leader, Researcher Deep Learning / AI

Jülich Research Centre (FZJ)

Jülich, Germany

Work group:

JSC – Jülich Supercomputing Centre



Area of research:

Scientific / postdoctoral posts



Job description:

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 HLST Teams across the Helmholtz centers and HAICU local partners to build up 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 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
  • 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.


Please apply via recruiter’s website.

Quote Reference: 2019-254

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