Postdoctoral Researcher in Multimodal Machine Learning for Precision Cancer Medicine

Postdoctoral Researcher in Multimodal Machine Learning for Precision Cancer Medicine

University of Helsinki

Helsinki, Finland

Project overview

This project aims to develop machine learning models for large-scale pan-cancer multiomics data. We build on our previous work (e.g., Sanjaya et al. Genome Medicine 2023; Pohjonen et al. arXiv 2024), developing the new models on the LUMI supercomputer and evaluating them on real-world data (e.g., in iCAN) in collaboration with precision cancer medicine experts. We strive to revolutionize cancer care through the power of massive data and machine learning!

Key responsibilities

• Design, implement and benchmark deep machine learning models for large-scale cancer datasets that include genomics, transcriptomics, epigenomics and imaging data
• Collaborate closely with experimentalists and clinical partners to understand and model biological processes and disease phenotypes
• Supervise and mentor students, and assist other team members in experiment planning, data processing and interpretation of results
• Contribute to writing scientific articles, conference presentations and grant applications
• Take part in open science and code sharing

Skills, expertise and qualifications

• A doctoral degree (PhD or equivalent) in computer science, data science, statistics, bioinformatics, or a related discipline
• A strong publication record in machine learning, computer science, bioinformatics, or computational biology
• Proficiency in Python and experience working in Linux-based HPC environments or cloud computing platforms
• Proven experience with deep learning frameworks such as PyTorch or TensorFlow, and familiarity with multimodal data fusion is highly desirable
• Familiarity with the AMD ROCm software stack is considered an asset
• Ability to work independently, as well as collaboratively in interdisciplinary and international research teams
• Excellent command of spoken and written English

Apply NowDeadline 31 August