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Our mission as research center: Discover personalized medical solutions for environmentally triggered diseases to promote a healthier society in a rapidly changing world.

In the Systems Genetics and Machine Learning Lab at the Institute of AI for Health (AIH) and the Helmholtz Pioneer Campus, we develop and apply machine learning solutions to analyse large clinical and molecular datasets addressing fundamental biomedical questions such as: Which are the molecular, cellular and organ-level traits associated with disease? Which ones are causative? Do they manifest in specific patient groups? Can we find interventions to revert these processes? We aim to leverage large biomedical cohorts and scalable machine learning approaches to further our understanding of human disease.

Given our strong focus on data integration, scalability and robustness, our research requires computational tools and infrastructure to enable reproducible machine learning experimentation and efficient data handling. As Staff Research Engineer (f/m/x) in the lab, you will be developing these tools, working at the interface of software engineering and data science, enabling researchers to be more productive.

Staff Research Engineer (f/m/x) 101612

Image Full time
Image Neuherberg near Munich
Image Postdocs

Your responsibilities

Examples of specific job responsibilities are:

  • Develop frameworks for running and tracking machine learning experiments;
  • Scale machine / deep learning models to big data settings;
  • Build and maintain workflows for the ingestion, preprocessing and analysis of molecular and clinical datasets;
  • Ensure secure and efficient data handling to enable scalable data analyses.

As an ideal candidate for this role you have significant software engineering skills while also having experience conducting machine learning research. Moreover, you feel eager about the opportunity of working in a cutting-edge scientific environment and contributing to impactful research outcomes.

Your qualifications

  • Ph.D. in Computer Science, Statistics, Mathematics, Physics or Engineering and scientific track record
  • Strong programming skills in Python, R, bash and git
  • Familiarity with cloud computing services (e.g., AWS or GCP) and workflow management tools or batch scheduling systems (e.g. SLURM)
  • Knowledge in Machine/Deep Learning with experience training neural networks in PyTorch (e.g., familiarity with distributed training)
  • Proficient in English

Beneficial Qualifications

  • Experience working with large-scale genomic data (e.g. UK Biobank, TOPMed, UK10K, etc.)
  • Experience with C/C++ or other compiled languages
  • Experience with optimising datasets and file formats for ML use cases (e.g. HDF5, Parquet, Zarr, etc)
  • Strong fundamentals in applied linear algebra and multivariate statistics
  • Experience with database languages (e.g., SQL)

What we offer you

work-life balance
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flexible working hours & working-time models
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continuous education and training
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30 days annual leave
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on-site health management service
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Image Leadership role in software/infrastructure projects
Image Opportunity to contribute to multiple scientific project
Image on-site nursery & holiday care
Image company pension scheme
Image discounted public transport ticket

Munich, with its numerous lakes and its vicinity to the Alps, is considered to be one of the cities with the best quality of life worldwide. With its first-class universities and world-leading research institutions it offers an intellectually stimulating environment.

Provided that the prerequisites are fulfilled, a salary level up to E 14 is possible. Social benefits are based on the collective agreement for the federal public service (TVöD). The position is (initially) limited to 2 years, under certain circumstances an extension can be arranged.

To promote diversity, we welcome applications from talented people regardless of gender, cultural background, nationality, ethnicity, sexual identity, physical abilities, religion and age. Qualified applicants with physical disabilities will be given preference.
If you have obtained a university degree abroad, we require further documents from you regarding the recognition of the degree. Please request the recognition as early as possible.

We are looking forward to receiving your comprehensive online application:


Interested?
If you have further questions, simply contact Francesco Paolo Casale, paolo.casale@helmholtz-muenchen.de, who will be happy to be of assistance.
Helmholtz Zentrum München
Deutsches Forschungszentrum für Gesundheit und Umwelt (GmbH)
AI for Health
Ingolstädter Landstraße 1

85764 Oberschleißheim

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