Researcher (m/f/d) in the field of Computational Science/Data Science at Universittsklinikum Dsseldorf
40225 Düsseldorf, Nordrhein-Westfalen, Germany -
Full Time


Start Date

Immediate

Expiry Date

26 May, 25

Salary

0.0

Posted On

27 Feb, 25

Experience

0 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

No

Skills

Good communication skills

Industry

Hospital/Health Care

Description

The University Hospital Düsseldorf (UKD) is the largest hospital in the state capital and one of the most
important medical centers in North Rhine-Westphalia. The 9,300 employees at UKD and its subsidiaries
are committed to ensuring that over 45,000 patients are treated inpatients and 270,000 receive
outpatient care annually. UKD stands for international excellence in patient care, research, and teaching,
as well as for innovative and safe diagnostics, therapy, and prevention. Patients benefit from the
intensive interdisciplinary collaboration of the 60 clinics and institutes. The special strength of the
university hospital lies in the close integration of clinical work and research for the safe application of
new methods. At UKD, the medicine of tomorrow is being created. Every day.
We are currently seeking a

SCIENCE

at the Institute of Pathology, effective immediately.
The position is initially limited until the project ends on March 31, 2026, under the terms of the
Wissenschaftszeitvertragsgesetz (WissZeitVG, according to § 2 (2)).
We are looking for an enthusiastic scientific employee (m/f/d) in the field of Computational Science/Data
Science to support our research projects. In this position, you will work on the digitization and analysis
of histological, molecular, and radiological data from cancer patients, with the aim of identifying new
therapeutically relevant subgroups.

Responsibilities
  • Collection and digitization of histological images
  • Generation of molecular datasets and their bioinformatic analysis
  • Curation of histological datasets and integration with radiological and molecular pathology

datasets

  • Conducting in silico analyses to identify clinically relevant subgroups
  • Contributing to the development of new analysis methods and tools for evaluating multimodal

data

Loading...