Data Scientist for Clinical Artificial Intelligence in Oncology (full-time)

  • Deutsches Krebsforschungszentrum
  • Heidelberg, Germany
  • 30/12/2021
Full time Data Science Artificial Intelligence Data Management Software Engineering

Job Description

Position: Data Scientist for Clinical Artificial Intelligence in Oncology (full-time)

Department: Junior Research Group "Digital Biomarkers for Oncology"

Code number: 2021-0423

The German Cancer Research Center is the largest biomedical research institution in Germany. With more than 3,000 employees, we operate an extensive scientific program in the field of cancer research.

Job description:

Our interdisciplinary working group aims to optimize deep learning algorithms as diagnostic assistance systems in oncology in order to enable long-term "tailor-made" care for patients with different kinds of cancer. We develop image analysis algorithms to analyse tumors in order to enable statements about tumor classification and/or tumor properties as biomarkers.

The current project has two main foci: to achieve an improved generalization ability of such algorithms on out-of-distribution data on the one hand and to increase interpretability or explainability of the "black box" CNN for the user on the other hand. This will greatly enhance usefulness and acceptance of such applications in the clinic. Once the XAI applications are in place, we will also investigate whether the use of such methods may serve to identify as yet unrecognized structures on histological slides or other images that can also be detected by human observers.

To support our dynamic team at DKFZ Heidelberg, we are looking for a data scientist to help develop and scientifically present the optimized digital biomarkers.

As a member of our team, you will independently research and implement processes to improve the explainability and generalization of neural networks. You will also generate your own scientific publications based on your results and actively support the interdisciplinary team regarding further research questions.

Requirements:

  • Successfully completed university studies (master / diploma) with a computer science background
  • Passion for “Research for a Life without Cancer”
  • Previous experience in the field of machine learning
  • Very good Python knowledge
  • Practical experience with PyTorch, TensorFlow, Keras or Scikit-learn
  • Ability to work both in a team and independently
  • Talent for organization as well as a high degree of flexibility and commitment
  • Ideally, previous experience in the AI areas of explainability, uncertainty and/or generalization
  • Ideally, first scientific publications in international journals
  • Enjoy building the workflow of a new project

We offer:

  • Interesting, versatile workplace
  • International, attractive working environment
  • Campus with modern state-of-the-art infrastructure
  • Salary according to TV-L including social benefits
  • Possibility to work part-time
  • Flexible working hours
  • Comprehensive further training program

Earliest Possible Start Date: as soon as possible

Duration: The position is initially limited to 2 years.

The position can in principle be part-time.

Application Deadline: 19.01.2022

Contact:

Dr. Titus Brinker
Phone 0151/75084347

Please note that we do not accept applications submitted via email.

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 (https://www.dkfz.de/en/stellenangebote/index.php).

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.