The Department Pulmonary Medicine in close collaboration with the department of Pathology and Clinical Bioinformatics, is seeking a PhD student with experience in the application of Machine and Deep learning models as part of our PNET-AID project. This is an excellent opportunity to develop deep learning technology to have direct impact on cancer research, with the aim to improve personalized treatment for patients.

The Department of Pulmonary Medicine is a large tertiary referral center for rare disease among which neuro-endocriene tumors of the lung and has a track record in research on this topic. The Department of Pathology and Clinical Bioinformatics 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. Our 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.

Your role is to develop and implement DL algorithms in the field of pulmonary neuroendocrine tumours (PNETs) in the Hanarth Fonds-funded PNET-AID research program and in close collaboration with Maastricht University Medical Center (MUMC+). You will apply artificial intelligence techniques to analyze digitalized (immuno)histopathological slides and also to combine more data types in one predictive model where necessary. These methods are aimed to assist decision making by pathologists and clinicians during tissue-based diagnostics and personalized treatment of PNET patients. This is an excellent opportunity to develop and apply cutting-edge DL technology to have direct impact on cancer research, thus supporting increasingly personalized treatment for our patients.

• You are a creative and enthusiastic researcher with a university degree in a relevant field (e.g. Bioinformatics, Biomedical Engineering, Computer Science) with some experience in computational (ideally histopathological) medical image analysis and deep learning.
• You are 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 have excellent communication skills including writing and presentation skills in English.
• Positive work attitude and team spirit is a must.

A challenging position within the largest University Medical Center (UMC) in the Netherlands with high ambitions in the field of healthcare, education and research.

• A temporary contract for a period of 4 years.
• The gross monthly salary is € 2.570,- in the 1st year and increases to € 3.271,- in the 4th year (scale OIO).
• Study options, such as participation in courses offered by the Netherlands Institute for Health Sciences (NIHES) or Molecular Medicine (MolMed).
• A 13th month's salary that will be paid out in November and a personal travel budget.
• A pension insurance with ABP. We contribute approximately 2/3rds of the monthly payment.
• Special benefits, such as a physiotherapist and a bicycle repair shop. There is also a sports club where you can work out after work.

The terms of employment are according to the Collective Bargaining Agreement for Dutch University Medical Centers (CAO UMC).

Erasmus MC

At Erasmus MC we are working to improve today's healthcare and tomorrow's health. We are pioneering, pushing boundaries and leading the way in research, education and care.

The Dingemans group is themed around clinical and translational research of thoracic malignancies with focus on biomarker driven lung cancer and neuro-endocrine tumors of the lung.

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 previous Hanarth Fonds-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.

You will be appointed at the department of pulmonary medicine and will be embedded in the Stubbs Group and responsible to Dr. Jan von der Thüsen (Pathology), Prof. dr. Dingemans (Clinical) and Dr. Yunlei Li (Bioinformatics).