Avis de recrutement : CERN recrute un(e) Scientifique des données basé à Genève en Suisse.

 

 

 

 

 

 

Job Description

Would you be willing become a key player in a novel AI-based tool to assist clinicians, patients and caregivers in the analysis, diagnosis and prognosis of diseases based on the integration of clinical and patient data over a Federated Learning (FL) infrastructure developed and hosted by CERN?

Your responsibilities

The Data and Image Analysis team in the Technology Department develops machine learning algorithms for particle physics accelerators infrastructure data analysis – to improve performances and provide robust modelling – as well as centralised and decentralised federated learning and distributed computing to provide robust, efficient and privacy preserving models for medical applications.

You will work on several projects to develop novel machine learning tools for anomaly detection, prescriptive maintenance, complex process simulations via GNN and algorithms for medical applications.

Furthermore, you will participate in an international collaboration to develop, deploy and operate a Federated Learning infrastructure hosted by CERN to enable multiple clinical and research infrastructure sites to collaboratively build trustworthy AI based predictive models to assist clinicians, patients and caregivers in the management of acute and chronic phases if ischemic stroke.

More information here: CAFEIN – Federated network platform for the development and deployment of AI based analysis and prediction models

Your profile

Skills and/or knowledge

  • Expert knowledge of common deep learning framewoks (e.g. Tensorflow, Keras, Pytorch) and programming techniques and languages: Python, SQL, C and Java.
  • Fluent in English, the ability to work in French would be an advantage.

Eligibility criteria:

  • You are a national of a CERN Member or Associate Member State.
  • You have a professional background in Computer Science (or a related field) and have either:
    • a Master’s degree with 2 to 6 years of post-graduation professional experience;
    • or a PhD with no more than 3 years of post-graduation professional experience.
  • You have never had a fellow or graduate contract before.

Additional Information

Job closing date: 16.07.2023 at 12:00 AM (midnight) CET.