At the Faculty of Medicine, Department of Clinical Medicine of the The University of Bergen (UiB), a full-time (100%) position as Postdoctoral Fellow is available for a period of three (3) years. The position is part of the project “Brain-Gut Microbiota Interaction in Irritable Bowel Syndrome: A multidimentional Appraoch” (http://braingut.no), financed by the Norwegian Research Council, the FRIPRO program. The position is anchored at The Norwegian National Center for Functional Gastrointestinal Disorders, Medical Department (www.helse-bergen.no/NKFM) and the newly established Mohn Medical Imaging and Visualization Center (https://mmiv.no), Department of Radiology, both situated at Haukeland University Hospital.

About the Project

There is increasing awareness that the brain and the gut are intimately linked, and that massive and diverse community of bacteria in the digestive tract aid digestion, regulates immune homeostasis and interacts with the central nervous system. In a clinical setting there has been great research interest in perturbations and dysfunction of the brain-gut-microbiota axis in functional gastrointestinal disorders. These new insights have been especially relevant to our understanding and treatment strategies of the widespread condition labelled irritable bowel syndrome (IBS). This project addresses research challenges in the following five key areas: (i) Brain structure and function and gastrointestinal motility in IBS, (ii) Cognition and emotion in IBS, (iii) Microbiota profiles in IBS, (iv) The importance of diet in driving IBS, (v) Patient phenotypes and identification of clinically useful molecular and imaging-derived biomarkers. For each of these areas, specific research questions are asked and organised as Work Packages. For image analysis we will apply next-generation techniques behind an ongoing revolution in both clinical and preclinical imaging: the machine learning methods deep neural networks (DNN) and convolutional neural networks (CNN). With top international collaborators (UCLA, Heidelberg, Nottingham, Adelaide) and being a multidisciplinary team of gastroenterologists, neuroscientists, nutritionist, clinical neuropsychologist, imaging specialists, geneticists, microbiologist, and data analysts, including three early career researchers, and access to an outstanding imaging infrastructure and The Norwegian Centre for Functional Gastrointestinal Disorders, we are in a very good position to advance the clinical science of IBS.

To successfully incorporate machine learning in medicine, the candidate will develop, implement, disseminate and evaluate machine learning techniques in the analysis of medical images and image-related data. The project aims to contribute to increased degree of personalized medicine and better decision support for diagnosis, prognosis and therapy in diseases and conditions where images are an important source of information.

Postdoctoral Fellow 

The candidate will work on both method development and applications.

• the candidate will work in a clinical environment and be a central member of our interdisciplinary research group consisting of clinical and biomedical researchers, mathematicians, statisticians and computer scientists. The candidate will have access to state-of-the-art imaging infrastructure, e.g. the most recent models from Siemens and General Electric (GE 3TMR 750 Discovery, Siemens Prisma 3T, Siemens Skyra 3T, Siemens Biograph mMR PET/MR (from Sept 2018), Siemens Vision PET/CT)
• the candidate will also have access to MMIV’s computational infrastructure, consisting of powerful desktop computers equipped with various NVIDIA GPUs (e.g. GeForce 1080Ti, Titan V). The hospital is in the process of establishing a novel high performance computing infrastructure which will be available for data analysis and machine learning
• the candidate will play an active role in introducing next-generation technology for medical image processing and analysis
• the candidate will also be encouraged to take part in the supervision of MSc and PhD candidates

For further information please contact Professor Arvid Lundervold, email: arvid.lundervold@uib.no, phone: +47 91561824.

Professor Trygve.Hausken, email: trygve.hausken@helse-bergen.no  phone: +47 90294882 or

Dr. Birgitte Berentsen, email:  birgitte.berentsen1@helse-bergen.no phone: +47 91545159.

Qualifications and qualities

We seek highly motivated individuals with experience applying machine learning to medical images.

• the applicant must hold a PhD or equivalent doctoral degree in medical/biomedical sciences or natural sciences on topics related to statistics, machine learning, computational medicine, bioinformatics or similar
• very good programming skills are a requirement. You are encouraged to include a link to your GitHub profile or similar documentation of programming competence in your application
• researchers who have experience in both machine learning and medical image analysis (with experience using for example scikit-learn, TensorFlow, PyTorch, Keras, scikit-image, R, MATLAB, ITK-SNAP, Nilearn, FreeSurfer) are particularly welcome to apply for this position
• the applicant must be experienced in counseling, teaching, writing manuscripts and preferentially also grant applications
• personal skills, including abilities to work independently and cooperate within a research group will be evaluated
• the applicant must be motivated and responsible, and also have a great work capacity and enthusiasm for research
• the applicant must be fluent in oral and written English. Experience with international collaboration is an advantage

We can offer

• a good and challenging work environment in research front of this field
• salary level 57 (code 1352/pay framework 24.1) at present NOK 490 900 gross p.a., with a degree in Medicine or Dentistry level 59 (code 1352/pay framework 24.3) at present NOK 508 800 gross p.a., with a medical specialization level 61 (code 1352/pay framework 24.5) at present NOK 527 500 gross p.a. on the government salary scale. Further promotion will be after service seniority in the position. A pension contribute of 2 % will be deducted and deposited to the state pension scheme. In the case of highly qualified applicant, a higher salary may be considered. Salary is under adjustment
• a good pension scheme in the Norwegian Public Service Pension Fund
• inclusive workplace (IW)
• good welfare benefits

For more information regarding what the University of Bergen can offer its employees please visit: http://www.uib.no/en/poa/74243/what-can-university-bergen-offer-its-employees