Mach aus dieser Rolle ein Bewerbungsgespräch — ein Lebenslauf und ein Anschreiben, die genau auf das zugeschnitten sind, was dieser Arbeitgeber sucht.
aiPTO in Heidelberg sucht eine/n Data Engineer/Scientist, der die Datenengine für multi-omics, digitale Pathologie, radiologische Bilder und klinische Daten entwirft, baut und skaliert. Du entwickelst eine AI-ready data atlas und arbeitest eng mit ML- und Computer-Vision-Teams zusammen.
Du bringst einen PhD oder MSc mit mind. 2 Jahren Erfahrung in Bioinformatik oder verwandten Feldern, beherrschst Python und Datenstrukturen, sowie Datenschutz.
aiPTO is a TechBio startup spun off from the German Cancer Research Center (DKFZ), taking on one of medicine's hardest problems: brain cancer. We are building a disruptive approach --- pairing next-generation patient-derived living tumor with fit-for-purpose virtual-tumor AI models. By recreating a patient's tumor biology in vitro and decoding it in silico, we aim to revolutionize brain cancer drug discovery and precision medicine. More details can be found on our publications (Individualized patient tumor organoids faithfully preserve human brain tumor ecosystems and predict patient response to therapy, DELPHAI predicts heterogeneous perturbation responses with learned single-cell fitness) and LinkedIn (https://www.linkedin.com/company/aipto/).
aiPTO has been selected as the data and AI partner of a newly funded Horizon Europe consortium that unites world-class neuro-oncologists, pathologists and drug-discovery pioneers across Europe. Together we are generating patient profiles of unprecedented depth: multi-omics, high-resolution digital pathology, 3D imaging and longitudinal clinical records, alongside single-cell drug-perturbation data from patient-derived organoids.
As the first member of our Heidelberg hub, you will build the data engine that turns these massive, disparate streams into AI-ready data atlas --- the foundation for virtual tumor models and agentic systems designed to predict patient-specific drug response, decode resistance and reveal drug mechanisms.