Job Detail

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 home.cern.

Diversity has been an integral part of CERN's mission since its foundation and is an established value of the Organization.

Job Description

The Neural Network Learning and Optimizations as a Service (NNLO-aaS) project aims at creating an end-to-end training and optimization platform for Deep Neural Networks, integrating external libraries (Tensorflow, Pytorch, Horovod) to existing CERN and CERN-related technologies (eos, cernbox, NNLO, etc. ) in a user-friendly software pipeline that could be used to establish a train-as-a-service platform. 

In this context, CERN is opening a two-years junior fellowship position for an expert in Computing Science with expertise on Software Containers, HPC job schedulers, Distributed computing with Message Passing Interface, Deep Learning training and optimization algorithms (Stochastic Gradient Descent, Bayesian Optimization, etc.) and libraries (Pytorch, Tensorflow, etc.). In addition, the candidate is expected to be familiar with Python and C++.

Qualifications

Eligibility criteria:

• You are a national of a CERN Member or Associate Member State;


• You have graduated, or are about to graduate with a university degree (BSc or MSc level in computer science,engineering or another relevant course) and have no more than 4 years’ relevant experience after obtaining your degree;


• Kindly note that experience prior to the latest obtained degree will not be taken into account for the calculation of your overall years of experience.

Essential skills and experience:

• You have knowledge in  Python and C++ programming languages and experience with Distributed Computing applications and Neural Network Training and Optimization;


• You value learning and sharing knowledge with colleagues, following best open-source collaborative practices and egoless programming;


• Passionate about software development and building and evolving robust, secure, well-tested software components and tools;


• You enjoy working in a small agile software development team building practical solutions in close collaboration with users and external partners.

Desired technical skills:

• ·Software Containers, HPC job schedulers, Distributed computing with Message Passing Interface, Deep Learning training and optimization algorithms (Stochastic Gradient Descent, Bayesian Optimization, etc.) and libraries (Pytorch, Tensorflow, etc.).

Please note that CERN Staff members are not eligible to apply for a Fellowship.

Additional Information

CERN would very much like to benefit from your expertise, commitment and passion.  

In return, CERN will provide you with:

• An employment contract for between six months (minimum) up to a maximum of 36 months.


• A stipend ranging from 5,305 to 6,586 Swiss Francs per month (net of tax).


• Coverage by CERN’s comprehensive health scheme (for yourself, your spouse and children), and membership of the CERN Pension Fund.


• Depending on your individual circumstances: an installation grant, family, child and infant allowances as well as travel expenses to and from Geneva.


• 2.5 days of paid leave per month.

Your Life @CERN

Get a glimpse of what it’s like to work at CERN: careers.cern/benefits and careers.cern/our-people

This is how you can apply:

You will need the following documents to complete your application:

• A CV;


• A scanned PDF of your most recent relevant qualification.

We recommend to add two recent letters of recommendation, giving an overview of your academic and/or professional achievements. You can upload these letters at the time of application if you have them to hand. You will also be provided with a link as soon as you have submitted your application to forward to your referees to upload their letters confidentially. Please note this must be done before the closing date.

All applications should reach us no later than 28 January 2021.