PhD candidate 'Artificial Intelligence to exploring the intersection of digital pathology and genetics in the gut microbiome'
PhD candidate 'Artificial Intelligence to exploring the intersection of digital pathology and genetics in the gut microbiome'
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Job description
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!
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.
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.
We offer you 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. An international work environment with an informal atmosphere.
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.
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.
We offer you 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. An international work environment with an informal atmosphere.
Specifications
- max. 36 hours per week
- €2789—€3536 per month
- Nijmegen View on Google Maps
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Radboud University Medical Center (Radboudumc)
Requirements
You are 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 geneticdata is a plus. Moreover you have good oral and written communication skills (in English).
Conditions of employment
Fixed-term contract: 4 years.
Working at Radboud university medical center means that you are ahead of the curve and working together on the healthcare of the future. And there is more. Our secondary terms of employment are impressive. These are fully tailored to you thanks to our Employment Conditions Selection Model. At Radboud university medical center, you will be given trust, and you will take the responsibility to handle everything together. We provide annual courses, both professional and personal.- A gross monthly salary between € 2.789 and € 3.536 (scale 10A) based on full-time employment.
- From 1 November 2023 the wages will increase by 4%.
- An annual vacation allowance of 8% and an end-of-year bonus of 8.3%.
- If you work irregular hours, you will receive an allowance.
- As a full-time employee (36 hours per week), you are entitled to approximately 168 vacation hours (over 23 days) per year.
- Radboud university medical center pays 70% of the pension premium. You pay the rest of the premium with your gross salary.
- Discount on your supplementary health insurance. You can make use of two collective health insurance policies: UMC Health Insurance and CZ Collective. They offer many extras to stay vital and healthy, such as a prevention budget, workshops, and apps.
In addition to our terms of employment, we also offer employees various other attractive facilities, such as childcare and sports facilities. Want to learn more? Take a look at the Cao UMC.
Employer
Radboudumc
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 and Ophthalmology.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.
Radboudumc
Welcome to Radboud university medical center (Radboudumc), where scientific breakthroughs are born through the curiosity and passion of our collaborating researchers in a vibrant environment. We believe trust and excitement are crucial elements to achieving our goals, and we approach our research as teams and with the utmost rigor to make a significant impact on health and healthcare. Our researchers are driven by their fascination with the biological, psychological, and sociological mechanisms underlying health and healthcare. They collaborate with partners from all over the world to improve health outcomes for all. Radboudumc unites patient care, research, education, and corporate learning, which allows us to approach our mission to shape the health and healthcare of the future in an innovative and person-centered way.
Our ambition is to lead the way in the pursuit of prevention, sustainability, meaningful care. We believe that through our research, we can significantly improve the health and well-being of society. Join us on our mission to make a difference in healthcare. Become a part of our community of gifted researchers, professionals or patient partners who are dedicated to making a real impact on population health and healthcare.
Read what it is like to do a PhD at the Radboud University Medical Center.
Read more about working at Radboud university medical center means.
Specifications
- PhD; IT
- Natural sciences; Health
- max. 36 hours per week
- €2789—€3536 per month
- University graduate
- 188243-P1325802-1
