PhD Student for Machine Learning in Oncology
Kennziffer: 2025-0004
- Frankfurt
- Full-time
- DKTK partner site Frankfurt/Mainz - Machine Learning in Oncology
„Forschen für ein Leben ohne Krebs“ – das ist unsere Aufgabe am Deutschen Krebsforschungszentrum. Wir erforschen, wie Krebs entsteht, erfassen Krebsrisikofaktoren und suchen nach neuen Strategien, die verhindern, dass Menschen an Krebs erkranken. Wir entwickeln neue Methoden, mit denen Tumore präziser diagnostiziert und Krebspatient:innen erfolgreicher behandelt werden können. Jeder Beitrag zählt – ob in der Forschung, in der Administration oder der Infrastruktur. Das macht unsere tägliche Arbeit so bedeutungsvoll und spannend.
Together with university partners at seven renowned partner sites, we have established the German Cancer Consortium (DKTK).
For the Research Group "Machine Learning in Oncology” (headed by Prof. Dr. Florian Buettner) at the DKTK partner site Frankfurt/Mainz and the Goethe University Frankfurt, we are seeking for the next possible date a
The Buettner lab (https://mlo-lab.github.io) works on the intersection of machine learning and oncology and as such is actively pursuing original research in both areas. Your PhD research at the intersection of machine learning, genomics and oncology will explore how machine learning solutions can be used to accelerate progress in personalized oncology.
Ihre Aufgaben:
Join us on an exciting new project aimed at understanding and modulating the tumor microenvironment (TME) in colorectal and pancreatic cancer via cutting-edge mRNA technology. Your PhD will focus on building and applying inherently interpretable deep probabilistic machine learning models for multimodal data integration. In collaboration with experimental and clinical partners from Mainz and Heidelberg, you will use these AI models to guide mRNA technology for modulating the TME, thereby helping to broaden the scope of mRNA technologies beyond its well-established application as vaccination. Through iterative cycles of data integration, hypothesis generation, and wet-lab feedback, you will help reveal key pathways that modulate therapy resistance and drive personalized immunological interventions.
Ihr Profil:
We are looking for a candidate with a background in computer science, statistics, bioinformatics or a related field (e.g. master’s degree in mathematics, physics, computer/date science, computational biology or related). A good knowledge of machine learning methods and statistics is essential, as is an interest in biomedical applications and cancer research; familiarity with probabilistic modeling and Bayesian methods is highly desirable. Good knowledge of programming/scripting languages (e.g. R or Python, knowledge of both is a plus) and best practices in software development as well as experience with Linux environments are required.
Experience with bioinformatics algorithms and applications is a plus.
The candidate will closely interact with other researchers and clinicians, therefore good English communication skills are also required.
Unser Angebot:
- Hervorragende Rahmenbedingungen: modernste state-of-the-art Infrastruktur und Möglichkeit zum internationalen Austausch auf Spitzenniveau
- Zugang zu internationalen Forschungs-Netzwerken
- Doktorandengehalt mit den üblichen Sozialleistungen
- 30 Tage Urlaub
- Flexible Arbeitszeiten
- Möglichkeit zur mobilen Arbeit und Teilzeitarbeit
- Familienfreundliches Arbeitsumfeld
- Nachhaltig zur Arbeit: Vergünstigtes Deutschland-Jobticket
- Entfalten Sie Ihr volles Potenzial: gezieltes Training und Mentoring durch das DKFZ International PhD Program und den DKFZ Career Service
- Unser betriebliches Gesundheitsmanagement bietet ein ganzheitliches Angebot für Ihr Wohlbefinden
Sie sind interessiert?
Prof. Dr. Florian Buettner
Telefon: +49 173 4613687
