PhD Research Fellow

PhD student position in multimodal artificial intelligence for healthcare

Artificial intelligence may significantly improve healthcare, offering the promise of precise and early disease detection. However, existing models primarily targets individual conditions using single modalities. To increase real-world impact, models need improved inference capabilities, encompassing phenotyping and identification of comorbidities.

This project provides a unique opportunity, where machine learning models will be built on a newly developed platform, integrated into the production systems at Akershus University Hospital. The integration enables data mining on real world data, compiling anonymized datasets from a vast set of sources, as well as seamless real-world testing. The core objective of the project is to go beyond traditional classification models, using unsupervised and/or multi-task learning on multimodal backbones.

The position is fully funded and the selected candidate will be supervised by Dr. Arian Ranjbar and Prof. Henrik Schirmer at Akerhus University Hospital and University of Oslo, in the research group Artificial Intelligence and Medical Informatics. The student will be part of a vibrant inter-disciplinary research team composed of data scientists, IT engineers and medical professionals.

Akershus University Hospital is a workplace with great diversity. We believe this is absolutely crucial to solving the tasks within patient treatment, research and development. We therefore want this diversity to be reflected among the applicants for our positions and encourage every qualified person to apply regardless of identity and background.

Major responsibilities

Qualifications

We are looking for a highly motivated person, well organized and dynamic with creative thinking.

To qualify for the position, you need:

• Master’s degree in either Engineering Physics, Engineering Mathematics, Electrical Engineering, Computer Science, or equivalent.
• Strong background in mathematics, and good programming skills (Python).
• Knowledge and experience with machine learning is an asset, along with familiarity in utilizing standard software engineering tools and cloud-based platforms.
• Excellent verbal and written communication skills in English. While not necessary, it is advantageous to know a Scandinavian language when working with the hospital databases.
• Ability to be inventive and to present novel ideas, data analyses and interpretation.

Personal skills

• We put strong emphasis on teamwork, as a successful data science project thrive on interdisciplinary interactions, and seek individuals who demonstrate personal suitability for effective collaborations.
• High intrinsic motivation and scientific curiosity
• Proactive, flexible, and problem-solving attitude

We offer:

• A full-time contract for three yearswith possibility for extension
• Start date upon agreement
• An exciting and stimulating academic environment
• Salary according as a PhD Research fellow according to Ahus regulations
• Attractive welfare benefits and a generous pension agreement, in addition to Oslo’s family-friendly environment with its rich opportunities for culture and outdoor activities

All applications must include:

• A presentation letter describing your motivationfor applying for the project and a PhD position
• A full CV (summarizing education, positions, academic work, scientific publications and other relevant activity)
• Transcripts and diplomas for bachelor's and master's degrees. (If you have not completed the master's degree, you must submit a confirmation that the master's thesis has been submitted).
• Copy of/link to master thesis and other scientific work you want us to consider
• Contact details of2-3 references(name, relation to candidate, e-mail and phone number)
• Only applications thorugh Webcruiter will be considered
  

Place of work

• The department is currently located at Lørenskog, Akershus University hospital.
• Excellent work-life balance and social goods

For more information, pleasecontact Arian Ranjbar (arian.ranjbar at medisin.uio.no)