CBmed GmbH: Scientific Researcher / Research Engineer (f/m/d)

Institut eHealth

Graz

Hybrid

EUR 18.000 - 24.000

Teilzeit

14 Tage+
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Zusammenfassung

CBmed GmbH in Graz seeks a part-time Scientific Researcher / Research Engineer (f/m/d) to join an interdisciplinary project at the intersection of Artificial Intelligence, Clinical NLP, and Precision Oncology. The role focuses on transforming pathology reports into clinically meaningful features and building an LLM-based extraction pipeline.

You will help integrate pathology-derived features with structured clinical data and contribute to the development of interpretable predictive models.

Aufgaben

  • Transform pathology reports into clinically meaningful features.
  • Develop an LLM-based extraction pipeline.
  • Integrate pathology-derived features with structured clinical data.
  • Develop interpretable predictive models.

Jobbeschreibung

CBmed GmbH: Scientific Researcher / Research Engineer (f/m/d)

Austria’s leading company - CBmed is a center for biomarker research in medicine with headquarter in Graz.

It links excellent research infrastructure, scientific expertise, medical knowledge, national and international industry partners for systematic medical biomarker research.We are seeking a highly motivated

Scientific Researcher / Research Engineer (f/m/d)

part-time, 14 hours per week for 12 months to join an interdisciplinary project at the intersection of Artificial Intelligence, Clinical NLP, and Precision Oncology. The project focuses on triplenegative breast cancer (TNBC) and investigates how large language models (LLMs) can
transform pathology reports into clinically meaningful features to support personalized treatment prediction.
The successful candidate will contribute to the development of an LLM-based extraction pipeline, the integration of pathology-derived features with structured clinical data, and the development of interpretable predictive models. The role is ideal for someone interested in research, scientific publishing, reproducible AI, and clinically impactful applications of machine learning.

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