Postdoc Artificial Intelligence for Improving Toxicological Pathology

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Postdoc Artificial Intelligence for Improving Toxicological Pathology

Background

In drug development, toxicological pathology plays an enormously important role in assessing which drugs are safe enough to progress to subsequent clinical trials. Toxicological pathologists have to go through thousands of slide per drug candidate to identify and grade potential toxic effects. Artificial intelligence has the potential to allow for more accurate and significantly faster analysis of toxicological screening studies.

This project is part of the European BigPicture project, which aims to establish the largest digital pathology repository in the world, with over three million images and associated diagnostic information. This type of data offers incredible potential for machine learning algorithms to impact pathology practice, but also requires sophisticated AI tools to get the most from this data. That is where you come in!

In this project you will develop new machine learning methods for end-to-end training on gigapixel-sized images, investigate AI explainability and transfer learning strategies. The application area for this project is toxicological pathology in drug development. You will work together with the over forty partners in the consortium which spans almost the entirety of Europe (and even further), including both academic partners, small, and big corporations. Within this project specifically, there is a close collaboration with UCB, mainly their research center in Slough, UK.

Tasks and responsibilities

  • Implement automated QA and tissue recognition algorithms.
  • Quantification and automated extraction of known biomarkers.
  • Work with weakly-supervised learning techniques to identify toxicological lesions (anomaly detection).
  • Collaborate with toxicological pathologists and other members of the BigPicture consortium.
  • Have fun interactions with colleagues, present at local and (inter)national conferences, and further develop yourself as an independent researcher.

Profile

You should be a creative and enthusiastic researcher with a PhD degree in a relevant field, such as medical image analysis, computer vision, or machine learning. You should have a clear interest to develop image analysis algorithms and an affinity with preclinical or medical topics. Good communication skills and expertise in software development, preferably in Python, are essential.

We offer

  • An exciting position in one of Europe's largest research groups in Computational Pathology.
  • 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 is a research group of the department of Pathology of the Radboud University Medical Center (Radboudumc). We are also part of the cross-departmental Diagnostic Image Analysis Group (DIAG) at Radboudumc, with researchers in other departments, such as Radiology and Nuclear Medicine, Pathology.

We develop, validate and deploy 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 and Panda grand challenges which we organized.

Radboudumc strives to be a leading developer of sustainable, innovative and affordable healthcare to improve the health and wellbeing of people and society in the Netherlands and beyond. This is the core of our mission: To have a significant impact on healthcare. To get a better picture of what this entails, check out our strategy.

Employment conditions

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 offer - A gross monthly salary between € 3.230 and € 5.088 (scale 10) 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%. - 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. - You get a discount on health insurance as well: you can take advantage of two group health insurance plans. UMC Zorgverzekering and CZ collectief. - We provide annual courses, both professional and personal. - 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.

Read more about the Radboudumc employment conditions and what our International Office can do for you when moving to the Netherlands.

Application

If you are interested, please apply via the following link

People

Francesco Ciompi

Francesco Ciompi

Associate Professor

Computational Pathology Group

Geert Litjens

Geert Litjens

Professor

Computational Pathology Group

Jeroen van der Laak

Jeroen van der Laak

Professor

Computational Pathology Group