The department is implementing deep learning methods to support the diagnostic and research work of pathologists and clinicians, including computer-aided diagnosis in a routine clinical setting. The PatHology Artificial iNtelligence plaTfOrM (PHANTOM) is an ongoing multidisciplinary cross-department project to deliver Deep Learning (DL) methodologies for diagnostic pathology, translational research and personalized medicine at Erasmus MC. Our DL approaches have been applied to determine diagnostic, prognostic and predictive biomarkers in collaborative projects, including oncology (e.g. pancreatic, lung), nephrology and dermatology. DL research application to histopathology and multi-omics have been developed by Dr. Li, Dr. Stubbs and Dr. von der Thüsen, driven by the requirements of our pathologists and our research laboratories (e.g. Tumour Immune Pathology Lab) to deliver personalized medical treatment decision support.
The role of the postdoctoral researcher is to further develop and implement DL algorithms beyond the capabilities already available in PHANTOM. The applicant will apply artificial intelligence techniques to analyze digitalized histopathological slides and also to combine more data types (including DNA, RNA and the digitalized histopathological sections) in one model where necessary. The candidate will be expected to take a leading role in PHANTOM by developing and implementing image analysis algorithms for ongoing and future diagnostics and research tasks in the department. These methods are aimed to assist decision making by pathologists and clinicians during tissue-based diagnostics and personalized treatment, in close collaboration with the Molecular Diagnostics group and Clinical Teams at Erasmus MC.
This is an excellent opportunity to develop and apply cutting-edge DL technology to have direct impact on cancer and immunopathology research, thus supporting increasingly personalized treatment for our patients
The Department of Pathology and Clinical Bioinformatics of the Erasmus University Medical Center (Erasmus MC) delivers digital histopathology, immunohistochemical, next-generation sequencing (NGS) and integrated bioinformatics solutions that are essential for the diagnosis. The pathologists are involved in all tumour- multidisciplinary meetings (MDM's) in the Erasmus MC where pathology results provide the basis of clinical decision support in the care lifecycle.
The von der Thüsen group is themed around biomarker research in thoracic pathology, with a specific focus on multimodality integration, including radiology-pathology integration and genomic, proteomic and multiplex immunohistochemical analysis. The Stubbs Group, in the department, develops DL applications for diagnostics and prognostics of cancer (including prostate, lung, pancreas and skin) and transplant rejection. Dr. Li and Dr. Stubbs have developed a deep learning framework, Multi-Omics DEep Learning for Prognosis-correlated subtyping (MODEL-P) in a Hanarth funded research program to deliver prognostic and predictive models for personalized (neoadjuvant) treatment in collaboration with Prof. C. van Eijck (Department of Surgery). Ongoing image and multi-omics deep learning projects include integrative, multi-modality analysis to predict disease progression (i-MAP) in collaboration with Dr. von der Thüsen in relation to lung cancer prediction and COVID-19.
The applicant will be embedded in the Stubbs Group and responsible to Dr. Jan von der Thüsen (Clinical) and Dr. Andrew Stubbs (Bioinformatics) to develop DL solutions for the diagnostic pathology researchers as well as interdepartmental collaborations, and tasked to co-develop the DL strategy in PHANTOM.
Qualifications and skills
- You should be a creative and enthusiastic researcher with a PhD degree in a relevant field (e.g. Bioinformatics, Biomedical Engineering) with >3 years experience in computational (histopathological) medical image analysis and deep learning.
- You will be expected to have excellent analytical skills, expertise in software development (Python) as well as expertise in deep learning model development (e.g. Tensorflow, Pytorch).
- You should have excellent communication skills including writing and presentation skills in English.
- Positive work attitude and team spirit is a must.
Before you apply please check our conditions for employment.
Terms of employment
- The initial contract will be limited to 2 years, with a potential for extension in case of successful project acquisition.
- You will receive a temporary position for 2 years. The gross monthly salary is € 4.901,- in the 1st year (scale 11.7) and increases to € 5.037,- in the 2nd year (scale 11.8).
- Study options, such as participation in courses offered by the Netherlands Institute for Health Sciences (NIHES) or Molecular Medicine (MolMed).
- Excellent fringe benefits, such as a 13th month that is already paid out in November and a personal travel budget.
- Pension insurance with ABP. The employer covers approximately 2/3 of the monthly contribution.
- Special benefits, such as a physiotherapist and a company bicycle repairer. And there is also a sports club where you can work on your fitness after work.
- Upon commencement of employment, we require a certificate of conduct (Verklaring Omtrent het Gedrag, VOG) and there will be, depending on the type of job, a screening based on the provided CV. Erasmus University Medical Center's HR Department will apply for this certificate on your behalf.
Information and application
For more information about this position, please contact Dr. Jan von der Thüsen, Pathologist, by phone:
+31(0)10 704 44 25) or e-mail email@example.com or Dr. Andrew Stubbs, Bioinformatician, by phone :+31(0)10 704 47 76 or e-mail: firstname.lastname@example.org.
If you are excited by the thought of this position and would like to apply, please do so by using the application form on our website.
No agencies please.