Postdoctoral Position in AI for Digital Pathology – EPFL – Lausanne, VD

EPFL

EPFL, the Swiss Federal Institute of Technology in Lausanne, is one of the most dynamic university campuses in Europe and ranks among the top 20 universities worldwide. The EPFL employs more than 6,000 people supporting the three main missions of the institutions: education, research and innovation. The EPFL campus offers an exceptional working environment at the heart of a community of more than 16,000 people, including over 12,000 students and 4,000 researchers from more than 120 different countries.

Postdoctoral Position in AI for Digital Pathology

Your mission :
The Signal Processing Lab (LTS4) at EPFL is seeking a candidate for a postdoctoral position in the field of AI for Digital Pathology. Your mission will be to lead and develop collaborative research at the frontiers of image processing, computer vision, machine learning and digital pathology for the analysis of histopathological images. More precisely, you will be responsible for driving the design and development of new machine-learning technologies for the classification and grading of tumoral cells in patients’ tissue images, as well as for the computation of novel interpretable biomarkers. You will be part of a highly interdisciplinary team that will work in close collaboration with the EPFL Center for Imaging and medical scientists and clinicians from the Lausanne University Hospital (CHUV).
Main duties and responsibilities include :
  • Conduct novel research at the intersection of machine learning, computer vision, and medical imaging (digital pathology).
  • Drive the development of advanced AI tools that provide standardized measures of the biomarkers of interest in histopathological images.
  • Transfer your research outcomes to medical partners at the Lausanne University Hospital (CHUV).
  • Publish and present scientific results in international conferences, workshops, and journals.
  • Participate in the supervision of Master’s and Ph.D. students.
Your profile :
You have a PhD degree in Computer Science, Electrical Engineering, or a closely related discipline. You have a solid scientific background and a proven publication record in machine learning, signal processing, data science and/or computer vision. You also show a strong interest in biomedical applications.
You have excellent programming skills in Python and a solid experience with the main software frameworks for learning-based processing (TensorFlow, PyTorch, JAX). Previous experience with the development of AI tools for medical imaging is a clear plus. You also have good organizational skills, including the ability to manage projects that involve multiple partners in a highly collaborative environment. Finally, you love to interact with scientists and partners from different domains and backgrounds.
We offer :
We offer a stimulating, cross-disciplinary scientific environment in a world-class research institution that is at the forefront of imaging science. EPFL ranks among the world’s top universities in computer science, and in machine learning in particular. The LTS4 is an internationally-recognized group that works at the frontier between signal processing, computer vision, machine learning and applied mathematics, with a special interest for biomedical applications. In this postdoc position, you will join and work in close collaboration with a dynamic team of scientists with strong interdisciplinary expertise in both LTS4 and the EPFL Center for Imaging. The working conditions at EPFL (competitive salary, social benefits, etc.) are excellent.

We look forward to receiving your application online. Applications via email or postal services will not be considered. For further information about the LTS4 and the EPFL Center for Imaging, please visit https://www.epfl.ch/labs/lts4/ and https://imaging.epfl.ch/

Start date :
The position is available immediately.

Term of employment :
Fixed-term (CDD)

Work rate :
100%

Duration :
1 year, renewable up to 2 years.

Remark :
Only candidates who applied through EPFL website or our partner Jobup’s website will be considered. Files sent by agencies without a mandate will not be taken into account.

Reference :
Job Nb 2083

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