Job
- Level
- Erfahren
- Job Feld
- Data
- Anstellung
- Vollzeit
- Vertragsart
- Befristetes Dienstverhältnis
- Ort
- Berlin
- Arbeitsmodell
- Hybrid, Onsite
Job Zusammenfassung
In dieser Position entwickelst du ein methodologisches Rahmenwerk zur Evaluierung anonymisierter Gesundheitsdaten und analysierst deren praktischen Nutzen für biomedizinische Forschung. Du implementierst neue Metriken zur Bewertung der kausalen Zuverlässigkeit und arbeitest mit K
Job Technologien
Deine Rolle im Team
- Develop and further refine a causally-grounded methodological framework for evaluating anonymized and synthetic health data in the context of the privacy-utility trade-off.
- Independently design new metrics to assess causal reliability ('causal utility') and analyze the effects of data-modifying procedures on causal identification and estimation.
- Investigate and evaluate anonymization and synthetic data generation methods with regard to their suitability for causal research questions in biomedical research.
- Apply, implement, and validate the developed methods using clinical and routine healthcare data from infrastructures of the Medical Informatics Initiative (MII) and the Network of University Medicine (NUM).
- Actively participate in a multi-site, interdisciplinary research consortium and independently contribute to and coordinate tasks relating to data access and governance.
- Actively contribute to scientific publications and to the development of tools and materials that support the application and use of the results in applied health research.
- Present the results at scientific conferences.
Unsere Erwartungen an dich
Ausbildung
- A successfully completed academic university degree (Master's or Diplom) in data science, medical informatics, biostatistics, bioinformatics, mathematics, epidemiology, health data science, or a related data analysis or computer science discipline.
Qualifikationen
- A strong interest in health data analysis research, digital medicine, and the application of modern methods to answer biomedical research questions.
- The ability to independently familiarize yourself with new methodological questions and address them in a structured manner.
- Strong programming skills in R and/or Python for preparing, analyzing, and visualizing complex biomedical datasets.
- Proficiency in reproducible analysis workflows, including version control, documentation, and transparent research practices.
- Very good written and spoken English; German language skills are not required but would be advantageous for engagement with national infrastructures and stakeholders.
- Strong teamwork and communication skills, as well as an independent, structured, and careful working style, a strong sense of responsibility, and initiative.
Erfahrung
- Experience working with complex or high-dimensional health data is desirable, as is an interest in causal inference methods and a willingness to become familiar with the relevant research approaches quickly.
Unser Angebot
- A varied job in a forward-looking research institute.
- Pay group E13 TVöD VKA-K. The classification is based on qualifications, the respective experience level is calculated on the basis of professional experience.
- Additional benefits customary in the public sector (including annual special payment, company pension scheme (VBL), capital-forming benefits).
- Flexible working hours and the option of working remote.
- 30 vacation days per year (with a five-day week).
- Various support offers to balance work and family life (childcare, cooperation with voiio).
- Training and further education opportunities.
- Mobile citizens' office on site.
- Corporate benefits (travel, leisure, shopping, etc.), Wellhub, JobRad.
- Very easily accessible and attractive workplace at the Spreepalais am Dom, Anna-Louisa-Karsch-Str. 2, 10178 Berlin.
Themen mit denen du dich im Job beschäftigst
Job Standorte
Das ist dein Arbeitgeber
Berlin Institute of Health
Das Berlin Institute of Health at Charité (BIH) ist eine etablierte Forschungseinrichtung, die biomedizinische Erkenntnisse in innovative medizinische Lösungen umsetzt. Es zielt darauf ab, klinische Beobachtungen in neue Forschungsansätze zu transformieren.
Description
- Unternehmenstyp
- Etablierte Firma
- Arbeitsmodell
- Hybrid, Onsite
- Branche
- Gesundheitswesen, Soziales
PhD Candidate BIH QUEST Center
- Ort
- Berlin
- Arbeitsmodell
- Hybrid, Onsite
- Diversität
- Für alle Personen geeignet (m/w/d)
- Nur Englisch
- Nur Englisch erforderlich
