Profile of PhD candidate for the research project: Genomic-radiomic assisted machine learning-based models to enable patient outcome prediction for personalized treatment in head and neck squamous cell cancer.
The rise of artificial intelligence methods (machine learning and deep learning) has already significantly impacted health care and clinical/tumour biology. Across all the fields of medicine, but especially in oncology, AI algorithms, trained on various diagnostic data, have been demonstrating the potential to unlock new biomarkers for prognosis and therapeutic response prediction. One of the next fields to be disrupted by artificial intelligence will be the integration of clinical medicine with radiomics and molecular biology.
This project will be carried out in the Netherlands Cancer Institute with generous funding by the Hanarth Fonds. The primary goal will be to build multimodal models (combining multiple imaging modalities and genetic data), and signatures for use in developing outcome prediction models in advanced head and neck squamous cell carcinoma. One of the main aspects of the imaging biomarker search will be investigating the link between molecular tumour biology characteristics, as captured by genomic data, and the tumour morphological phenotype, as quantified by the imaging data.
The task of the PhD student will be to coordinate prospective data gathering, perform and assist in MRI image analysis analysis, and via machine learning techniques, link tumour genomic data with radiomics and possibly other clinical data. For complex cancer types like HNSCC, integrating multiple data sources for machine learning models will revolutionize the development of predictors, provide better insights into potential connections and play a key role in optimization treatment.
We are looking for a motivated, goal-oriented, independent, and proactive PhD candidate or postdoc who is enthusiastic about working in a multidisciplinary setting. You will develop novel deep learning algorithms and shape the research in collaboration with the project leaders, AI, and medical experts.
Preferably you have a master's degree in artificial intelligence, computer science, physics, mathematics, or equivalent by experience. In any case, you should have experience with deep learning and have excellent programming skills.
You will work in a dynamic international scientific environment and collaborate with colleagues at the Antoni van Leeuwenhoek Hospital, the NKI and at other institutes. PhD students can enter the Amsterdam Oncology graduate school.
The gross salary per month will range between € 2.882 to € 3.322 according to the PhD salary scale and depending on previous experience. The terms of employment will be in accordance with the CAO Ziekenhuizen (Collective Labor Agreement for Hospitals). In addition you will receive a fixed end-of-year bonus in December (8,33%) and in May you will receive 8,33% holiday pay. For more information in regard to the secondary conditions please visit our website: https://www.nki.nl/careers-study/how-to-apply/
Please send your application in via our website, applications sent directly to e-mail will not be processed. Furthermore we would like to receive 1 single PDF file with all documents listed below:
A motivation letter that explains why you are interested in our vacancy and joining our team;
The names and contact addresses of at least two references;
A complete record of Bachelor and Master courses (including grades and explanation of grading system);
A list of projects and publications you have worked on (with brief descriptions of your contributions, max 2 pages);
A separate research statement where you explain your initial ideas, e.g., how would you propose to start the research. We are not looking at this stage for working solutions, creativity is appreciated.
Affinity with deep learning and the other required techniques should be clear from the materials submitted and your GitHub account. Applications missing any of the above materials will be desk rejected. An assessment may be part of the procedure. There is no application deadline. Applications will be processed as they come in.
The NKI values diversity and is committed to creating an inclusive work environment that stimulates the best in each individual. Applications of all individuals are welcomed regardless of age, ancestry, religion, disability, distance from the labor market, sexual orientation or gender identity.