Postdoc (f/m/d) AI-based automated adaptation and biological optimization o at HelmholtzZentrum DresdenRossendorf
Dresden, , Germany -
Full Time


Start Date

Immediate

Expiry Date

14 Dec, 25

Salary

0.0

Posted On

16 Sep, 25

Experience

0 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

No

Skills

Good communication skills

Industry

Hospital/Health Care

Description

With cutting-edge research in the fields of ENERGY, HEALTH and MATTER, around 1,500 employees from more than 70 nations at Helmholtz-Zentrum Dresden-Rossendorf (HZDR) are committed to mastering the great challenges facing society today.
At the Institute of Radiooncology – OncoRay scientists (f/m/d) specializing in medicine, physics, biology and IT work together to crucially improve the treatment of cancer by administering radiation therapy that is biologically-personalized and technically-optimized.
The Department of Medical Radiation Physics is looking for a Postdoc (f/m/d) AI-based automated adaptation and biological optimization of proton therapy.

Responsibilities
  • You will push the limits of translational medical physics research in hot-topic proton therapy projects. In close collaboration with colleagues from other institutions and our clinical team, you will establish biologically optimized proton therapy treatments by implementing methods for considering the variable biological effectiveness of protons based on NTCP modelling, identified risk factors and the LET.
  • Of equal importance is your key contribution to our focus project of realizing online-adaptive proton therapy, enabled by an AI driven, fully automatized feedback loop of imaging, PGI-based treatment verification and fast adaptation. Therefore, you will develop efficient machine-learning models for fast, automated data processing and decision support, e.g. regarding the identification of adaptation needs.
  • You are expected to publish in peer-reviewed journals and participate in international conferences. The supervision of students and doctoral candidates and the application for funding are self-evident tasks.
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