Mapping the Origins of Chromosomal Instability in Cancer
Research Focus
Why do some tumors vanish from the immune system right before they metastasize? Chromosomal instability (CIN), responsible for immune evasion, therapy resistance, and metastatic spread, is the prime suspect. It silences a tumor's interferon signaling and clears the way for invisible spread. This project investigates the mechanistic origins of CIN through AI-native cancer systems biology, building the system that reads that silence: a multimodal model trained on genomics, imaging, and histology, predicting and ultimately targeting CIN-driven metastasis in cancer patients.
Your tasks
- Architect the computational core of the lab's multimodal AI system, working alongside the wet-lab scientists generating its training data
- Curate and harmonize multimodal training data, spanning WES/WGS, bulk and single-cell RNAseq, spatial transcriptomics, whole-slide histology, PET/CT imaging
- Mine WES/WGS and RNA-seq data from patient cohorts and extend this lens to whole-slide histology, quantifying tumor neural innervation and integrating it with PET/CT imaging
- Stress-test model predictions against experimental and clinical outcomes, in close collaboration with the lab's international network
- Publish first-author results in leading peer-reviewed journals and present them at international conferences
What we are looking for
- A computer scientist with real command of artificial intelligence and machine learning (MSc in computer science, artificial intelligence, or data science)
- Fluency in Python and hands-on experience with PyTorch, JAX, or TensorFlow
- A demonstrated ability to drive an AI/ML project independently, end to end
- Experience with transfer learning or foundation models is a plus
- Experience building multimodal deep learning systems that combine genomic, imaging, and tabular data in a single model is a strong plus
- Familiarity with multi-omic and imaging data integration (e.g., WES/WGS, bulk and single-cell RNA-seq, spatial transcriptomics, digital pathology/whole-slide imaging, PET/CT) is a plus
- Fluency in collaborating across disciplines, with scientists and clinicians alike
- Excellent written and spoken English
We offer
- A fully funded position (75%, ~30 hours/week) with a current annual gross base salary of EUR 39,649.05 per the university collective agreement; this may increase based on relevant prior experience
- A 4-year contract
- Participation in a novel, emerging research program bridging multimodal AI systems, chromosomal instability, and interferon biology
- Close collaboration with the lab's wet-lab and clinical teams, grounding every computational prediction in experimental and patient data
- Access to computational, genomic, and imaging infrastructure within Medical University of Innsbruck
- Research visits and joint projects with the lab's European and US collaborators (City of Hope, UC San Diego) and its US industry partners
How to apply
Please send your application, including your CV and a brief cover letter describing your motivation and relevant experience, to bewerbung@i-med.ac.at, with jan.pencik@i-med.ac.at in copy. Please quote the reference number MEDI-21223 in the subject line.
