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Physik Bioinformatik Mathematik Informatik Wissenschaftliche/r Mitarbeiter/in Baden-Württemberg Forschungseinrichtung

  • Scientist Position (f/m/d) in the Heidelberg AI Health Innovation Cluster

    17.12.2021 Deutsches Krebsforschungszentrum (DKFZ) / German Cancer Research Center Heidelberg Scientist Position (f/m/d) in the Heidelberg AI Health Innovation Cluster - Deutsches Krebsforschungszentrum (DKFZ) / German Cancer Research Center - Logo
  • Research Associate (f/m/d) Deep Learning Segmentation in Biomedical Imaging: An Unsupervised and Self-Supervised Approach

    11.05.2023 Karlsruher Institut für Technologie (KIT) Karlsruhe Research Associate (f/m/d) Deep Learning Segmentation in Biomedical Imaging: An Unsupervised and Self-Supervised Approach - Karlsruher Institut für Technologie (KIT) - Logo
  • Research Associate (f/m/d) Deep learning segmentation for biomedical imaging using interactive and active learning

    11.05.2023 Karlsruher Institut für Technologie (KIT) Karlsruhe Research Associate (f/m/d) Deep learning segmentation for biomedical imaging using interactive and active learning - Karlsruher Institut für Technologie (KIT) - Logo
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Scientist Position (f/m/d) in the Heidelberg AI Health Innovation Cluster

Veröffentlicht am
17.12.2021
Bewerbungsfrist
31.01.2022
Vollzeit-Stelle
Deutsches Krebsforschungszentrum (DKFZ) / German Cancer Research Center
Heidelberg
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The DKFZ is committed to increase the proportion of women in all areas and positions in which women are underrepresented. Qualified female applicants are therefore particularly encouraged to apply.

Among candidates of equal aptitude and qualifications, a person with disabilities will be given preference.

To apply for a position please use our online application portal (www.dkfz.de).

We ask for your understanding that we cannot return application documents that are sent to us by post (Deutsches Krebs­forschungs­zentrum, Personal­abteilung, Im Neuen­heimer Feld 280, 69120 Heidelberg) and that we do not accept applications submitted via email. We apolo­gize for any inconvenience this may cause.
The German Cancer Research Center (DKFZ) is advertising

10 Scientist Positions in the Heidelberg AI Health Innovation Cluster

(Ref-No. 2021-0400)

Apply for a scientist position within the “AI Health Innovation Cluster” Staff Scientist Program.

The newly established “AI Health Innovation Cluster“ in the Rhine-Neckar Metropolitan Region combines the excellence and expertise of several renowned research and health institutions to concentrate and excel the existing research potential in modern health sciences. DKFZ, EMBL, the Max Planck Institute for Medical Research, Heidelberg University and the University Clinics Heidelberg and Mannheim as well as the Central Institute for Mental Health have joined forces to promote cutting-edge research for AI applications in medicine and health. The AI Health Innovation Cluster is an activity within "Heidelberg Mannheim Health & Life Science Alliance".

Description:
The Staff Scientist Program of the cluster offers research positions in the highly dynamic and exciting area between AI and medical research. You will be part of an interdisciplinary and vibrant research environment that is pioneering research in machine learning and information processing. The dedicated research projects available within the program will provide the opportunity to participate in the development of a diverse range of state-of-the-art methodology and software components. You have the possibility to dive into computing and software engineering, or to work with machine learning and cloud technologies. The program provides state-of-the-art technical infrastructure and networks, but also individual support towards career development.

We look forward to your application, if you can see yourself making a big difference at the interface of AI and medicine.

Requirements:
We are looking for candidates holding a degree (Master or comparable) in computer science, mathematics, engineering, physics or related quantitative sciences (e.g. bioinformatics or medical informatics). Communication skills and the ability to work in a multidisciplinary international team will be expected. Your analytical and software development skills are essential. Experiences with either machine learning and associated software stacks, high-performance computing environments or cloud technologies are beneficial.

Application procedure:
The application will be two-stage. In the first stage, please submit your complete application (in English) as one single PDF file via our online application portal. This application document should comprise your curriculum vitae, a one-page statement of interests, a copy of the latest degree certificates (originals, transcripts and translations if applicable) and optionally a publication list and up to two letters of recommendation.

In a second stage, upon invitation you will have the opportunity to prioritize your favorite projects in a matching procedure between projects and candidates. Available projects will be advertised on the AI Health Innovation Cluster web page (see below). The selection process is coordinated by the DKFZ. Candidates who are selected by the committee will be offered a position at the partner institution where the selected project is based.

The cluster offers:
  • A fully-funded position with competitive remuneration at one of the seven participating institutions according to the applicable regulations of the respective institution
  • Join the large international community across the partner institutions
  • Make use of state-of-the-art research facilities and infrastructure
  • Manage your own career development with training courses and career support
  • Share ideas and meet colleagues in the active network
For further detailed information please visit: AI Health Innovation Cluster (https://www.aih-cluster.ai)

Contract period:
The positions are initially limited to 2 years with the possibility of prolongation.

For further information please contact
Prof. Dr. Klaus Maier-Hein, phone +49 (0)6221/42-2354.
Application deadline: 31.01.2022
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