Data Engineer Scientist – Multimodal Clinical Data Integration & AI (mfd)

aiPTO is a TechBio startup spun off from the German Cancer Research Center (DKFZ) taking on one of medicines 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 patients 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 ( project

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.

• Architect the scientific data engine: design build and scale the infrastructure that unifies multi-omics spatial transcriptomics digital pathology radiological imaging and clinical data

• Make data AI-ready: harmonise and standardise multimodal datasets for deep-learning models and agentic workflows working hand-in-hand with our machine-learning and computer-vision scientists

• Bridge the disciplines: be the link between wet-lab researchers clinical oncologists and IT scientists translating biological questions into data schemas

• Own rigour and compliance: implement biomedical metadata standards and GDPR-grade governance for sensitive patient data

• PhD or MSc with 2 years of experience in bioinformatics computational biology computer science biomedical engineering or a related quantitative field

• Demonstrated mastery in structuring and integrating complex biological or clinical datasets; hands-on experience with real-world patient data is a strong plus

• Depth in at least one modality multi-omics spatial biology digital pathology or medical imaging and familiarity with biomedical metadata standards

• Advanced Python and modern software-engineering practice; experience with database architecture data tooling for biological workflows or AI coding assistants is highly valued

• A pioneering mindset: self-driven curious and motivated by turning advanced technology into real patient impact in an agile startup

• Direct patient impact: your work feeds models built for an aggressive cancer with few options every well-structured dataset moves us closer to patient-matched therapy

• Founding leadership: as our first Heidelberg team member you shape the technology stack the architecture and the hub

• World-class network: close collaboration with DKFZ leading European clinical centres and international consortium partners

• Package and trajectory: competitive compensation hybrid working and a career path that accelerates as aiPTO scales