Background
Every day, clinics worldwide generate vast amounts of digital data on health and pathology. Digital pathology alone, with its high-resolution imaging of tissue samples, creates terabytes of data. This data offers an improved understanding of disease morphology and tissue phenotype. At the same time, genetic sequencing contributes extensive datasets, mapping the intricate web of tissue genotype and potential mutations, and metagenomics provides insight into encoded functions within the fecal and tissue microbiome. Lastly, brain imaging delivers rich data on brain structure and function, which could potentially lead to a deeper understanding of human (mental) health. Together, these data sources open opportunities to comprehensively understand diseases, from the visible tissue changes down to the molecular level. One example is understanding how gut microbiome organization (histology) and composition (genetics) correlate with genetic changes in the host(human genetics), and how do these combined changes influence gut health and disease susceptibility as well as brain function.
However, despite the immense potential these disciplines present, we only partially understand their intricacies. The sheer volume and complexity of the data often obscure subtle mechanisms that underpin mechanisms of health and disease. By using Artificial Intelligence (AI), we can analyze large-scale multimodal data and aim at connecting characteristics extracted from histological and genetic data.
PhD position
We are looking for a PhD candidate to work within an EU-funded project, aiming at building a federated platform to investigate mechanisms of the gut-brain axis at the intersection of digital pathology and genetics (microbiome & host).
If you are passionate about these disciplines and want to grow in a stimulating international academic environment, you might be our new colleague!
During your PhD trajectory, you will develop and validate multimodal AI models based on neural networks to analyze digital pathology, genomics and microbiomics data of the gut and brain data. Particular focus will be on multimodal AI models for gut diseases, such as IBD and spirochetosis, and brain diseases, such as ADHD and psychiatric disorders. Most developed models will be made available through the web-based platform developed within the project. For this, you will use functionalities provided by the grand-challenge.org platform, an open-source project developed and maintained by the Research Software Engineering (RSE) team at Radboudumc.
Profile
We are looking for: - A creative and enthusiastic researcher with a master degree in a relevant field, such as artificial intelligence, computer vision, machine learning, data science. - A person with a clear interest to work with AI algorithms and that has an affinity with medical topics. Experience with laboratory work (histology/immunohistochemistry) and/or genetic data is a plus. - Someone with good oral and written communication skills (in English).
We offer
- An exciting position in one of Europe's largest research groups in Computational Pathology, at the crossroads with the Cancer Microbiology Group embedded within the department of Pathology of the Radboudumc and collaborating with the Cognitive Neuroscience Department of the Radboudumc and the Donders Institute for Brain, Cognition and Behaviour.
- An international work environment with an informal atmosphere.
- 4-year contract of 36 hours per week (full time).
- Salary scale 10A.
- An annual vacation allowance of 8% and you will receive an end-of-year bonus of 8.3%.
- 168 vacation hours (over 23 days) per year.
- 70% coverage of the pension premium by Radboudumc. You pay the rest of the premium with your gross salary.
- A discount on health insurance.
Organisation
The Computational Pathology Group (CPG) and the Cancer Microbiology Group (CMG) are research groups of the department of Pathology of the Radboud University Medical Center (Radboudumc). The CPG develops, validates and deploys novel medical image analysis methods, usually based on the newest advances in machine learning with a focus on computer-aided diagnosis (CAD). Application areas include diagnostics and prognostics of breast, colon, prostate and lung cancer. Our group is among the international front runners in the field, witnessed for instance by the highly successful CAMELYON, PANDA and TIGER grand challenges which we organized. The CPG is also part of the cross-departmental Diagnostic Image Analysis Group (DIAG) at Radboudumc, with researchers in the departments of Radiology and Nuclear Medicine, Pathology, Cardiology, Radiotherapy and Neurology.
The CMG aims at preventing cancer development and progression by increasing our understanding of the gut microbiome and how it keeps us healthy as well as the underlying mechanisms for its role in cancer development. We develop tools to use the mucosal tissue microbiome as predictor or prognostic factor of gut diseases.
In this EU-funded project we collaborate with the Cognitive Neuroscience Department of the Radboudumc and the Donders Institute for Brain, Cognition and Behaviour.
Employment conditions
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. Radboud university medical center’s HR Department will apply for this certificate on your behalf.
Read more about the Radboudumc employment conditions and what our International Office can do for you when moving to the Netherlands.
Application
To apply for this PhD vacancy, follow the official application procedure at this link. Apply before October 20, 2023.
