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Helmholtz Zentrum München is a research center with the mission to discover personalized medical solutions for the prevention and therapy of environmentally triggered diseases and promote a healthier society in a rapidly changing world.

At our institute you will find a scientifically stimulating international environment. Together with renowned scientists and supported by an excellent infrastructure you will have the opportunity to make an important contribution for a healthier society.

The research group:

The Machine Learning group, at the Helmholtz Institute of Computational Biology, applies state-of-the-art artificial intelligence methods to study different biological systems at the single cell level. This call is for a postdoctoral fellow to study host-pathogen interactions using spatially-resolved, single cell multi omic data and machine learning techniques. Our aim is to understand how cellular communication circuits control the host immune response against the invading pathogen and how these circuits can serve as the basis to identify novel drug targets and develop novel diagnostic tools. Working at the interface of single cell biology, medicine and machine learning; we collect multiple data modalities from tissues and integrate them with clinical data from patients, linking the cellular mechanisms operating in the tissue at the moment of infection with the patient's clinical history.

Project summary:

Tuberculosis (TB) is one of the top causes of death worldwide and it is responsible for 1.5 million deaths each year. As part of the UNITE4TB initiative, a joint industry-academic effort to develop and test novel, relapse-free cures for TB, the group uses biological samples and clinical data from patients at different stages of TB to identify biomarkers that can be predictive of infection outcome and that can serve as the basis for novel diagnostic tests. The group applies state-of-the-art machine learning techniques to link the single cell data with different biomedical data types.  

For this project we have an exciting postdoctoral position for candidates with backgrounds in computational biology, data science, computational epidemiology and machine learning. 

The successful candidate will develop and deploy machine learning workflows that will allow for the integration of multiple data modalities and the transfer of learning between them. The goal of these workflows will be to identify biomarkers with potential predictive power to help clinicians to diagnose and monitor disease progression. In collaboration with wet-lab scientists and clinicians working on the field, the candidate will have the opportunity to contribute to the design at multiple stages of the study and generate the appropriate genomic and clinical data. 

Postdoc on computational biology in the Machine Learning Group (f/m/x) 101076

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Image Neuherberg near Munich
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Your responsibilities

Aims: Some of the specific aims of the project include, but are not limited to:

  • Characterising cellular circuits involved in the onset of M. tuberculosis infection
  • Developing machine learning methods for the integration of single cell genomics with clinical data, including X-rays, MRIs and clinical records
  • Developing machine learning methods for the mapping of transcriptional and epigenetic programms onto spatial transcriptomics platforms (i.e: 10X Visium, in situ sequencing).

Key experience and competencies:

Postdoctoral Training Fellows are expected to lead their own projects, contribute to other projects on a collaborative basis (both in the lab and with external collaborators) and guide PhD students in their research. We are looking for a bold, imaginative, open and dynamic candidate, with strong motivation to face some of the most outstanding challenges in the fields of medicine and machine learning. 

Your qualifications

Essential:

  • PhD (or in the final stages of PhD submission) in computational biology, computer science, systems biology, biological engineering, robotics, computational epidemiology or related fields
  • Proven knowledge and experience in computational biology or machine learning. The candidates must submit their github repositories as part of the application. Good programming skills in Python are essential.  
  • Experience with text mining and natural language processing
  • Knowledge of deep learning packages such as Tensorflow, PyTorch, or JAX
  • Experience with optimizing and tuning neural network architectures and interest in developing novel architectures
  • Experience with generative models, such as GANs  
  • Ability to work independently and as part of a small team
  • Strong oral and written communication skills, with emphasis in data visualisation and communication
  • Enthusiasm and initiative to develop new skills and to take interdisciplinary approaches to scientific questions 

Desirable:

  • Experience with image processing and analysis
  • Experience in mathematical and statistical modelling
  • Experience with graph neural networks
  • Experience with software development practices (Agile, versioning, etc.)
  • Experience with decentralized decision making and exploratory systems (Particle swarm, cellular automata etc.) 
  • Experience with reinforcement learning and agent based modelling

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 home office options
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Image company pension scheme
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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.

Remuneration and social benefits are based on the collective wage agreement for public-sector employees at federal level (TV EntgO Bund). The position is (initially) limited to 3 years, but 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.
Applicant guidance on the Corona pandemic

Interested?
If you have further questions, simply contact Dr. Carlos Talavera-López, 49023, who will be happy to be of assistance.
Helmholtz Zentrum München
Deutsches Forschungszentrum für Gesundheit und Umwelt (GmbH)
Institute of Computational Biology
Ingolstädter Landstraße 1

85764 Oberschleißheim

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