Data Scientist

Company Description
At CERN, the European Organization for Nuclear Research, physicists and engineers are probing the fundamental structure of the universe. Using the world's largest and most complex scientific instruments, they study the basic constituents of matter - fundamental particles that are made to collide together at close to the speed of light. The process gives physicists clues about how particles interact, and provides insights into the fundamental laws of nature. Find out more on http://home.cern.

Job Description
Introduction

Are you a Data Scientist and Machine Learning enthusiast willing to take an active role in designing, developing and implementing novel machine learning algorithms in the field of accelerator technologies and medical applications?

Would you like to contribute to the mission of assisting engineers to improve the performances of accelerators and clinicians in the diagnosis, prevention and management of diseases? Then join CERN and take part in supporting knowledge transfer to society of machine learning algorithms used in the accelerator technology field.

You will join:

-the Data and Image Analysis team in the Technology Department which is responsible for the development and implementation of 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
-a H2020 funded European project that proposes a novel, trustworthy by design, and privacy-preserving AI-based platform to develop algorithms to assist clinicians, patients and caregivers in the management of acute and chronic phases of ischemic stroke
-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.

Functions

As a Data Scientist and Machine Learning Expert, you will work within an international collaboration of international experts in the accelerator technology and medical fields.

You will have access to large and diverse datasets, challenging problems, cutting edge accelerator technology and clinical research and developments.

Your main activities will consist of:

-Collection of the requirements to be translated in project and research activities.
-Design, development and implementation of machine learning algorithms and federated learning (FL) infrastructures in the accelerator technology and medical fields.
-Development and optimisation of the infrastructure and network design with respect to performance, robustness, availability, efficiency and scalability.
-Implementation, testing, and validation of the algorithms and FL infrastructure.
-Configuration and support of big data FL platforms: architecture, evolution, migration, upgrades and patches, including monitoring of system health and performance, to ensure high levels of performance, availability, and security.
-Sharing domain and technical expertise, providing technical mentorship and training to peers and students.
-Publishing and reporting results and achievements in scientific journals.

Qualifications
Master's degree or equivalent relevant experience in the field of Computing Science or a science discipline (e.g. Mathematics, Physics) with significant computing content, or a related field.

Experience:

The successful candidate should have demonstrated experience in following fields:

1.Building machine learning solutions
2.Building and optimising data analysis infrastructure towards performance, robustness and scalability.
3.Coding in one or more languages (such as, but not limited to Python, Java) and knowledge of data structures, algorithms, and software design
4.Configuration and operational support of big data infrastructure to ensure high levels of performance, availability, and security.

Additional experience in following fields would be an asset:

-Working with distributed machine learning and in particular federated learning
-Collection of users requirements to be translated in project and research activities

Technical competencies:

-Knowledge of common deep learning framewoks (e.g. Tensorflow, Keras, Pytorch).
-Knowledge of programming techniques and languages: Python programming is required; SQL, C and Java knowledge would be an advantage.
-Knowledge of data lakes and warehouse concepts, technical architectures, infrastructure components, extract transform load (ETL), and reporting or analytic tools and environments (e.g. Hadoop, Spark)

Behavioural competencies:

-Solving Problems: identifying, defining and assessing problems, taking action to address them
-Achieving Results: delivering high quality work on time and fulfilling expectations
-Working in Teams: building and maintaining constructive and effective work relationships
-Communicating Effectively: delivering presentations in a structured and clear way; adjusting style and content to the audience; responding calmly and confidently to questions
-Learning and Sharing Knowledge: keeping up-to-date with developments in own field of expertise and readily absorbing new information

Language skills:

Spoken and written English or French: ability to understand and speak the other language in professional contexts, or the undertaking to aquire it rapidly.

Additional Information
Eligibility and closing date:

Diversity has been an integral part of CERN's mission since its foundation and is an established value of the Organization. Employing a diverse workforce is central to our success. We welcome applications from all Member States and Associate Member States.

This vacancy will be filled as soon as possible, and applications should normally reach us no later than 05.03.2023 at 12:00 (mid-day) CET.

Employment Conditions

Contract type: Limited duration contract (4 years). Subject to certain conditions, holders of limited-duration contracts may apply for an indefinite position.