Working for the Ecole polytechnique fédérale de Lausanne (EPFL) means being part of a prestigious school that consistently ranks among the top 20 universities worldwide. As a public university dedicated to improving the world around us, we have three missions: training, research and technology transfer. We boast one of the most dynamic university campuses in Europe and employ more than 6,000 people. Our employees perform high-value-added work in teaching and research and in the school’s administrative and technical services. Between our main campus in Lausanne and our satellite campuses in Geneva, Neuchâtel, Fribourg and Sion, our workforce is composed of more than one hundred different professions.
At EPFL, we foster a culture of respect and inclusion in the workplace. We promote a healthy work-life balance through flexible working hours and on-campus daycare and sports facilities. Our employees also benefit from belonging to a diverse community of 16,000 people – including over 10,000 students and 3,500 researchers – from 120 different countries.
Machine Learning / Deep Learning Engineer (BBP)
Your mission :
The EPFL Blue Brain Project (BBP), situated on the Campus Biotech in Geneva, Switzerland, applies advanced neuroinformatics, data analytics, high-performance computing and simulation-based approaches to the challenge of understanding the structure and function of the mammalian brain in health and disease. The BBP provides the community with regular releases of data, models and tools to accelerate neuroscience discovery and clinical translation through open science and global collaboration.
For our Machine Learning Team, we are currently seeking to fill the following position:
Machine Learning / Deep Learning Engineer Main duties and responsibilities include :
Contribute to the development of Machine Learning and Deep Learning applications for the automation and acceleration of the Blue Brain Project scientific activities
Document, communicate, and present quantitative analyses and results to managers and internal partners
Your profile :
Advanced degree (MSc or PhD) in a quantitative field—e.g. Computer Science, Applied Mathematics, Data Science
At least 2 years of work experience
Strong personal motivation, interest in the field, and eager to learn.
Required skills :
Very good familiarity with Python programming langage
Very good familiarity with UNIX operating system
Good familiarity with a lower-level programming language—e.g. C++, Java, Scala, …
Good understanding of Applied Statistics techniques
Good understanding of Machine Learning and Deep Learning models and principles
Good familiarity with Python libraries for Machine Learning: numpy, sklearn, pandas
Good familiarity with at least one framework for the development of Deep Learning applications—e.g. TensorFlow, Keras, Torch, Caffe, Theano, …
Good team player
Fluent English in speech and writing
Excellent presentation skills
Preferred skills :
Familiarity with running applications on supercomputers and Slurm
Familiarity with Apache Spark framework and Big Data technologies
Familiarity with NLP and/or Computer Vision applications
Familiarity with Time Series modelling and methods
Professional experience in software development life-cycle including unit testing, continuous integration, debugging and documentation
We offer :
An internationally visible and rising project in simulation-based research
A young, dynamic, inter-disciplinary, and international working environment
State-of-the-art hardware dedicated to the development of Machine and Deep Learning applications
