Postdoctoral Fellow – AI, Biomedical Imaging & Statistical Genetics

This four-year fellowship within the Amgen Research & Development Postdoctoral Program works at the intersection of biomedical imaging, artificial intelligence and human genetics at Amgen deCODE genetics in Reykjavík. The fellow helps build a quantitative atlas of human anatomical diversity from population-scale data spanning MRI, CT, DXA, retinal imaging, mammography, genomics, proteomics, transcriptomics and longitudinal clinical phenotypes, and uses it to uncover biological mechanisms, identify potential therapeutic targets and develop imaging-based biomarkers for drug discovery and precision medicine.

The work develops and validates AI and machine-learning methods for automated image segmentation, representation learning and extraction of quantitative image-derived phenotypes, performs genetic association and statistical analyses to characterise the genetic architecture of these phenotypes, and builds reproducible workflows for large-scale imaging and genetic analysis, using GPU and CPU computing for model development, in collaboration with scientists across Amgen deCODE genetics and Amgen Research.

A PhD completed before the start date in engineering, artificial intelligence, computer science, bioinformatics, mathematics, biostatistics, biomedical engineering or a related quantitative discipline. Preferred: a strong publication record; expertise in artificial intelligence, machine learning, biomedical image or signal processing, statistical genetics, biostatistics or computational genomics; experience with large-scale imaging, genetic or multi-omic data; proficiency in Python, R, C/C++ or similar languages; experience with deep-learning frameworks and modern image-analysis methods; Linux and high-performance or GPU computing.