PhD fellowship in clinical oncology with a focus on medical image analysis

Department of Oncology, Rigshospitalet and Dept. of Clinical Medicine, Faculty of Health and Medical Sciences, University of Copenhagen

Dept of Oncology, Rigshospitalet invites applicants for a PhD fellowship in large scale analysis of time series of images in cancer patients undergoing radiotherapy. The project is part of a larger research project entitled Self-supervised artificial intelligence for large scale analysis of longitudinal images in oncology, which is financed by the Independent Research Fund Denmark.

Start date is expected to be January 1, 2024 or as soon as possible thereafter.

The project

We are initiating a dual PhD program to study large scale methods of machine learning and their potential value in clinical decision making. This posting is for a PhD candidate with medical background to work in parallel with a PhD student with computer science background. The PhD project is rooted in a busy oncology clinic and an important aspect of the medical PhD work is to facilitate that clinical relevance is front and center of the project, despite the technical nature.

Machine learning and in particular deep learning (DL) have the potential to change how images are interpreted and processed in medicine. Most DL systems learn to solve problems in a supervised manner directly from examples of input and output and often many manually labeled examples of output are needed to get to a satisfactory performance. Unfortunately, abundance of data is rare in medical imaging, instead, what is often available is a limited number of simply labeled scans from a single study/institution severely limiting supervised learning. Gathering large amounts of unlabeled data is easier. Images gathered during cancer treatment and specifically radiotherapy is an excellent source of such unlabelled data because multiple images and multiple imaging modalities are used for diagnostics, treatment planning, treatment delivery, and finally follow-up. This becomes dozens of 3D scans for each patient and tens of thousands per year per radiotherapy center.

The medical PhD candidate will work closely together with the computer scientist to test whether novel self-supervised artificial intelligence techniques can be used to analyze the daily images during a course of radiotherapy (typically 6 weeks of daily irradiation) and answer pertinent medical questions. There is some flexibility on matching the clinical application on the interest of the successful candidate. However, two important aspects are:

Predicting risk of recurrence based on treatment images

Hypothesis: AI analysis from self-supervised training can be adapted to provide clinically relevant predictions of risk of recurrence after one year based on available imaging data acquired during treatment

and

Predicting cardiotoxicity based on treatment images

Hypothesis: The AI algorithm developed by the computer scientist can be trained to provide clinically relevant estimates of cardiotoxicity following radiotherapy from the available imaging data acquired during treatment.

Who are we looking for?

We are looking for candidates with a background in medicine and able to be enrolled in the PhD program at Faculty of Health and Medical Sciences at University of Copenhagen. Please confer the admission requirements here.

 In addition, the ideal candidate might have

• Experience in oncology, ideally with a proven interest in radiotherapy,
• a creative, solution-oriented mindset and able to work both independently and in research teams,
• a wish to apply advanced computer science and machine learning techniques in medicine,
• good language skills, the group is international and fluency in spoken and written English is a requirement,
• other relevant professional activities.

What are we offering

• An interesting, but challenging, PhD project at the intersection of AI and medicine rooted in a clinical environment.
• A supervision team of MD, medical physics and computer scientists.
• Participation in a group of approximately 20 PhD students in Dept of Oncology with adjacent office space and collaborations.
• Opportunities for conference participation to present results of your PhD work.
• Fully salaried PhD position according in accordance with Danish labor laws.

Further information

Primary supervisor:             Ivan Richter Vogelius
Phone:                                + 45 35459885 or 51538834
Email:                                  ivan.richter.vogelius@regionh.dk
Ivan Vogelius is medical physicist and professor

Medical supervisor:             Jeppe Friborg
Phone:                                + 45 35458189
Email:                                  jeppe.friborg@regionh.dk
Jeppe Friborg is senior consultant at Dept. of Oncology

Computer science supervisor: Jens Petersen
Phone:                                + 45 60687733
Email:                                  phup@di.ku.dk
Jens Petersen is associate professor in Computer science with a 50/50 split position between the computer science department at Copenhagen University and Rigshospitalet.

Based on background education and seniority, your salary, pension and terms of employment will be settled in accordance with the existing agreement between the Danish Regions (Danske Regioner) and the relevant professional organization.

Application deadline: 30 November 2023 23.59pm CET.

• Fakta

• Arbejdssted
  Rigshospitalet, Blegdamsvej
• Kontaktperson
  Ivan Vogelius
• Adresse
  Blegdamsvej 9, 2100 København Ø
• Stillingstype
  Læge
• Speciale
  Klinisk onkologi
• Ansættelsesform
  Tidsbegrænset periode
• Ugentlig arbejdstid
  Fuld tid
• Ansættelsens start
  01-01-2024
• Regionens jobnr.
  252610
• Quick-nr.
  455897
• Indrykningsdato
  06-11-2023
• Ansøgningsfrist
  30-11-2023 (udløbet)