PhD Candidate Artificial Intelligence (AI) for Endometrial Cancer Diagnostics
Whether a patient with endometrial cancer still receives radiation or chemotherapy after removal of the uterus is mainly based on an assessment of the tumor by the pathologist. The Pathology Department of the LUMC will investigate how we can improve this assessment with the help of artificial intelligence. Do you have the knowledge and experience to make this research a success?
- Albinusdreef, Leiden, Zuid-Holland
- Tijdelijk contract / Tijdelijke opdracht
- Uren per week:
- 36 uur
- € 2495 - € 3196 per maand
Endometrial (uterine) cancer is the most common gynaecological cancer in the Western world, with more than 100,000 new patients annually in Europe alone. Fortunately, the majority of these patients can be cured by surgical removal of the uterus. However, a major problem in treatment is that it is difficult to predict which patients will benefit from additional treatments, such as radiotherapy and/or chemotherapy. A promising new branch of cancer research is the use of artificial intelligence for improved diagnostics. Recent examples show that computers are perfectly capable of recognizing patterns in microscopic images and can also connect them to predictions. As of now, this has never been used for endometrial cancer and we want to investigate whether artificial intelligence can support and even improve current diagnostics and risk assessment. We have the unique opportunity to use the world's largest tumor tissue bank consisting of endometrial tumors from women who have participated in the PORTEC studies. The LUMC has the necessary computers, servers and storage space to realize the plans in this project. As a PhD student, you will be the linchpin of the AIR-MEC project team, where you will receive additional support from a postdoc hired specifically for this project as well. You will create AI models which, based on microscopic images, can predict which molecular changes are present in the tumor, which treatment the tumor will react to, and models which can predict the patient’s prognosis. AIR-MEC goes even further, as you will also figure out through which image parameters your AI models can predict. You will continue to molecularly examine these potentially unknown but important tumor properties, so that you can contribute to a better understanding of endometrial cancer. The AIR-MEC team is comprised of world experts in the field of endometrial cancer diagnosis and treatment, who will assist you in the correct clinical interpretation and long-term implementation of the developed models.
· You'll work with experts in endometrial cancer diagnosis and treatment and artificial intelligence
· You will develop AI-driven computer models based on microscopic images of the world's largest endometrial cancer dataset
· This research is unique and has not been carried out before
· The models you develop will improve diagnosis, treatment and therefore the outcomes of patients with uterine cance
We are looking for an enthusiastic and dedicated colleague with some experience in programming and an affinity with machine learning and AI-driven computer models. You hold a master's degree in (technical) medicine, artificial intelligence, computer science, data science or similar. Experience or affinity with oncology, gynecology, pathology or molecular biology is not a must, but definitely an advantage. You are able to empathize with clinical issues and have good communication skills. You have a proactive and inventive mindset and want to use the next four years to improve future diagnostics and treatment of patients with endometrial cancer.
As a PhD candidate, you will be appointed for the duration of four years. Your salary is a maximum of € 2.495 in the first year, amounting to a maximum of € 3.196 in the final year (scale PhD students, Collective Labour Agreement University Medical Centers).
For this AIR-MEC study we have received a grant from the Hanarth Fund. This fund wants to promote and improve the use of artificial intelligence and machine learning to improve the diagnosis, treatment and outcome of patients with cancer. AIR-MEC is carried out in collaboration with pathologist Viktor Koelzer from the University of Zurich, Jouke Dijkstra from the Department of Radiology and Carien Creutzberg from the Department of Radiotherapy.
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Contact: dr. Tjalling Bosse, medical specialist, department Pathology
+31 (0)71 526 66 21