PhD Position in Artificial Intelligence for Biomedicine
Core
Architecting a multimodal AI system to predict and target chromosomal instability-driven metastasis in cancer patients by integrating genomics, imaging, and histology data.
Role type
PhD researcher (AI/ML in cancer systems biology)
Builds
Multimodal deep learning models combining genomic, imaging, and tabular data
Domain
Biomedicine / Oncology / Artificial Intelligence
Deliverable
production ML models
Required skills
Artificial intelligence, machine learning, Python, PyTorch, JAX, TensorFlow, transfer learning, foundation models, multimodal deep learning, multi-omic data integration, digital pathology, PET/CT imaging analysis
Preferred skills
Experience building multimodal systems combining genomic, imaging, and tabular data
Technologies
PyTorch, JAX, TensorFlow, WES/WGS, RNA-seq, spatial transcriptomics, whole-slide histology, PET/CT
Responsibilities
Architect the computational core of the lab's multimodal AI system, curate and harmonize multimodal training data, mine genomic and imaging data from patient cohorts, stress-test model predictions against experimental and clinical outcomes, publish first-author results in peer-reviewed journals
Seniority
PhD level, independent researcher
