Scientific Associate in Diagnostics – Onco-Genetics / Somatics | Wissenschaftliche(r) Mitarbeiter*in (m/w/d) im Bereich Befundung – Onko-Genetik / Somatik
amedes MVZ Trägergesellschaft Göttingen mbH
Job Summary
This role involves contributing specialized expertise to patient-oriented genetic diagnostics, focusing on molecular (hemato-)oncology and somatic genetics. The Scientific Associate will be responsible for generating diagnostic reports crucial for individual therapy planning. Key daily tasks include analyzing Next-Generation Sequencing (NGS) data, liquid biopsy results, and other somatic genetic analyses using modern technologies. A core part of the job is the continuous optimization of NGS evaluation pipelines and active participation in developing new analytical procedures to expand the diagnostic portfolio. Candidates should possess a degree in Biology or a related natural science, professional experience in molecular pathology/oncological diagnostics, and proficiency with specific laboratory information systems (GePaDo, MOLIS) and specialized genetic databases (Varvis, QCI). This position offers the opportunity to work in a high-standard, quality-focused environment (ISO certified) and actively shape the future of genetic diagnostics within a leading European medical diagnostic group.
Required Skills
Education
Completed degree in Biology or a comparable natural science study program. A doctorate (PhD) is welcome but not mandatory.
Experience
- Professional experience in (hemato-)oncological or molecular pathological diagnostics
- Expertise in molecular biological and genetic procedures, particularly NGS
- Experience working with peripheral blood, bone marrow, and FFPE samples
- Ability to safely evaluate somatic variants according to WHO and Tier classifications
- Desirable: Experience in report generation considering therapeutic options
Languages
Additional
- Work location is Hannover, Germany. Must adhere to certified quality management systems and maintain high responsibility when handling sensitive patient data.
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