The Department of Pathology at the Clínica Universidad de Navarra (Pamplona, Spain) is seeking a pre-doctoral student or post-doctoral fellow with experience in machine learning and scientific programming. The candidate will work with a multi-disciplinary team of researchers, including bioinformaticians, pathologists, oncologists, and computer scientists, and conduct original research on computational pathology.

Digital pathology images contain rich information on complex diseases. The goal of our efforts is to build and apply automated analytical pipelines for various types of pathology data, including histopathology images and multi-omics (e.g., genomics, epigenomics, transcriptomics, and proteomics) information. The candidate will help to develop a deep learning-based solution that uses scanned H&E whole slide images (WSIs), which are routinely used for clinical diagnosis, for predicting tumor recurrence or response to treatment or mutation status without immunohistochemical analysis and molecular testing.

Qualifications

Hands-on in Biomedical Informatics, Computational Biology, Computer Science, or a related field is required. Substantial experience in machine learning, Python and R programming, and familiarity with deep learning packages (e.g., TensorFlow, Keras, or PyTorch) are essential. Strong problem-solving and communication skills are highly desirable for this opportunity.

Responsibilities

The pre-doctoral student will develop and refine machine learning methods for analyzing histopathology, clinical, and multi-omics data, collaborate with our multi-disciplinary team, and publish the findings.

What do we offer?

The position will be based at Clínica Universidad de Navarra, Pamplona (Navarra).

The candidate will work in an environment of scientific excellence, impact research and a good environment.

Compensation package will consist of salary and benefits, which will be in accordance with qualifications and experience.