Cambridge Residency Programme: Postdoctoral Researcher - Deep Learning for Inverse Problems

54 Minutes ago • All levels • Artificial Intelligence

About the job

Job Description

This postdoctoral researcher position at Microsoft Research Health Futures focuses on deep learning for inverse problems in healthcare. Responsibilities include designing, implementing, evaluating, and deploying new machine learning methods and models for processing medical instrument signals and improving diagnostic measurements. The role involves collaboration with clinical experts and the broader Microsoft Research community, publication of research findings, and contributing to the team's ambitious research agenda. The ideal candidate will possess a strong understanding of deep learning frameworks (e.g., PyTorch) and have experience with digital signal processing or medical image reconstruction. A PhD or equivalent research experience in a relevant field is required.
Must have:
  • PhD in relevant field
  • Deep learning experience (PyTorch)
  • Software engineering skills (git)
  • Passion for healthcare
  • Publication record
Good to have:
  • Digital signal processing expertise
  • Medical image reconstruction experience
  • Multimodal transformer experience
  • Biomarker discovery experience
  • Experience with real-world healthcare data
Perks:
  • Industry-leading healthcare
  • Educational resources
  • Product and service discounts
  • Savings and investment plans
  • Maternity/paternity leave
  • Generous time away
  • Giving programs
  • Networking opportunities

Overview

Microsoft Research Health Futures conducts world-class research at the intersection of AI and healthcare, drawing on deep expertise in signal processing, biomedical imaging and deep learning. We are seeking a motivated postdoctoral researcher to join our vibrant team of researchers and engineers.

 

We focus on the development of models that can process raw medical instrument signals and improve diagnostic measurements and biomarker extraction. As a postdoctoral researcher within our team, you will have the opportunity to:

  • Deepen your expertise in biomedical image reconstruction and AI.
  • Explore multi-modal models for digital signal processing.
  • Conduct experimentation with world-class computational resources.
  • Grow in a team with a strong culture of collaboration and rigorous research.

Qualifications

Required/Minimum Qualifications:   

  • PhD degree (or on-track to complete), or equivalent expertise in independent research, in areas such as computer science (e.g. machine learning, deep learning, signal processing), electrical engineering, computational biology, medicine.
  • Prior experience with deep learning frameworks (e.g., PyTorch) and software engineering practices (e.g. git).
  • Passion for healthcare and medicine.
  • Ability to work and learn in a collaborative and diverse environment.

Preferred/Additional Qualifications:

  • Expertise in any of the following topics:
    • Experience with digital signal processing and/or medical image reconstruction.
    • Design and evaluation of large multimodal transformers.
    • Biomarker discovery (broadly interpreted).
  • Experience with real-world healthcare data
  • Track record of publication in top conferences or journals, such as: NeurIPS, ICML, ICLR, CVPR, EMNLP, Nature (and affiliated, e.g. NPJ Digital Health), JAMA, Radiology AI, Lancet Digital Health etc.

Responsibilities

The ideal candidate will have strong intellectual curiosity and passion to solve real-world problems in healthcare using machine learning. Responsibilities will include:

  • Design, implement, evaluate and deploy new machine learning methods and models.
  • Share your research with the broader research community through publication or open sourcing.
  • Collaborate with clinical experts and across Microsoft Research.
  • Work as part of a team to advance our ambitious research agenda.
Benefits/perks listed below may vary depending on the nature of your employment with Microsoft and the country where you work.
Industry leading healthcare
Educational resources
Discounts on products and services
Savings and investments
Maternity and paternity leave
Generous time away
Giving programs
Opportunities to network and connect
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