Senior Imaging/Digital Pathology Expert- Roche Information Solutions Data Services – Roche – Basel, BS


Who We Are

At Roche, we are passionate about transforming patients’ lives and we are fearless in both decision and action – we believe that good business means a better world. That is why we come to work each day. We commit ourselves to scientific rigor, unassailable ethics, and access to medical innovations for all.

We do this today to build a better tomorrow!

Role Purpose

As a Senior Imaging/ Digital Pathology Expert you will be part of the RIS Data Science Technology team. You will play an essential role in creating a highly efficient environment to drive information extraction and data abstraction from unstructured data sources like digital pathology images. You will contribute fundamentally to bringing together sophisticated diagnostic and treatment data from medical devices and IT systems to improve research outcomes and patient care.

Your main responsibilities will include :
  • Collaborate with various teams to shape the development of our image analysis/ information extraction/ data abstraction platform into the Roche landscape of FAIR data and services.

  • Collaborate with various teams to implement innovative methods to generate new insights from images and other unstructured data & incorporate them into the Roche Information Solutions product portfolio

  • Implement innovative AI mechanisms and pipelines to annotate imaging data

  • Engage with internal key customers to understand business needs and to supply high-quality image analysis techniques and services

  • Support the automation of pipelines and implement intelligent processes for QA.

  • Innovate and bring forward creative solutions in your area of responsibility and beyond

  • Participate in pre-competitive initiatives to drive the implementation of image analysis in the diagnostics & pharma industry.

As Senior Imaging/ Digital Pathology expert you bring:
  • Extensive and demonstrable hands-on experience with computer vision techniques and deep learning frameworks

  • Strong curiosity about biomedical imaging and the translation of state-of-the-art research into clinical applications.

  • Experience with OCR technologies & graph convolutional neural networks is a plus

  • You know how to run computationally demanding simulations and analyses with large amounts of data on the cloud; preferably AWS.

  • University Degree in Data Science related fields, ideally a Ph.D degree (in Statistics, Computer Science, Mathematics, Bioinformatics or similar academic field) or equivalent industry experience

  • Strong collaboration skills

  • Ability to work in changing, agile, multinational and multiple location environment

  • Very good communication and presentation skills

  • Proficiency in English


We@RocheDiagnostics is the mindset and culture we as Diagnostics colleagues strive to adopt to help achieve our vision and realize our strategy. The dimensions are:

  • We are passionate about our customers and patients

  • We radically simplify

  • We trust, collaborate & have fun

  • We ALL lead

  • We experiment & learn

You are expected to demonstrate the We@RocheDiagnostics dimensions and help evolve the functions culture beliefs, beginning it to life as part of the TransformD journey.

Application process

Please apply with your CV & a cover letter. The application window will close on the 7th of January.


The role will be based in Basel or Penzberg.

At the Company’s discretion, an exception to the location requirement could be made under extraordinary circumstances.

As this position is a global role, international business travel will be required depending upon the business location of the successful candidate and ongoing business project activities.

Roche is strongly committed to a diverse and inclusive workplace. We strive to build teams that represent a range of backgrounds, perspectives, and skills. Embracing diversity enables us to create a great place to work and to innovate for patients.

Roche is an equal opportunity employer.

Job Level:

Individual contributor


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