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Researcher / HPC Software Engineer (f/m/d) for Deep / Machine Learning
Published(193 days ago)
Deadline for applications(173 days ago)
Forschungszentrum Jülich GmbHJülich
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
Two Researchers and HPC Software Engineers for Deep / Machine Learning
conduct 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 ML/DL community
stay abreast of current trends and best practices in configuration and distributed execution 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 / DL 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
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
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)
beneficial would be experience with High Performance Computing (HPC, also GPU-based) and corresponding workflows and toolchains (Slurm, MPI, etc)
very good knowledge of English in written and spoken form
ability to present your work at workshops and international conferences
opportunity to work on interesting challenges 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)
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