Skip to content  

Working at TU/e

Post-doctoral fellow on automatic machine learning (V32.4006)

Post-doctoral fellow on automatic machine learning

Challenging post-doctoral fellowship on automated machine learning (AutoML). We are building an AutoML playground (an 'AutoML Gym') to train AutoML systems on many different problems and get increasingly better over time. This work is part of an Amazon Research Award.
Position
(Post-doctoral) Researcher
Irčne Curie Fellowship
No
Department(s)
Department of Mathematics & Computer Science
Institutes
Data Science Center Eindhoven
FTE
1,0
Date off
30/08/2019
Reference number
V32.4006

Job description

We are seeking a highly creative and motivated post-doctoral fellow to join the Data Mining Group at the Eindhoven University of Technology. The candidate will be working in collaboration with Dr. ir. Joaquin Vanschoren, as well as the OpenML core team and Amazon Research. 

The field of automated machine learning (AutoML) aims to automatically build machine leaerning models in a data-driven, objective, and automatic way. The user simply provides data, and the AutoML system automatically determines the approach that performs best for this particular application. Although the field is moving fast and substantial progress has been made, it is also hindered by a lack of benchmarking and a lack of environments for experimentation and analysis.

We are building an AutoML playground (an 'AutoML Gym') to train AutoML systems on many different problems and get increasingly better over time. Similar to the OpenAI Gym, which trains reinforcement learning agents on many different scenario's, the AutoML Gym will train and test many different AutoML systems (agents) on many challenging problems. We will continuously track the performance of the AutoML agents, and store this information in a meta-data repository, a shared memory that can be accessed by any AutoML agent to perform meta-learning and become increasingly better over time.

The project will progress in three phases, first covering hyperparameter optimization to automatically construct and optimize machine learning pipelines as efficiently as possible. Next, we enable meta-learning, by giving AutoML agents access to a shared memory of prior experiments. Finally, we will include AutoML techniques that design neural architectures, covering both few-shot learning and neural architecture search.

This work is funded by an Amazon Research Award. It will be set in an very interactive environment, including the Eindhoven Data Mining Group, the OpenML team, the AutoML community, and Amazon research.

Job requirements

We are looking for a motivated candidate with:

  • A Doctorate in Computer Science (or similar)
  • Advanced knowledge of machine learning techniques
  • Prior experience in meta-learning or automatic machine learning is an asset
  • Strong mathematical and analytical skills
  • Excellent programming skills. Experience with open source development is an asset
  • Excellent communication skills in spoken en written English
  • Creativity, free thinking, perserverance

Conditions of employment

We offer:

  • A challenging job for 12 months in a dynamic and ambitious university and a stimulating research environment;
  • A gross salary per month between € 2709 and € 4274 (based on a fulltime appointment), depending on experience and knowledge in accordance with the Collective Labor Agreement of the Dutch Universities.
  • 8% holiday allowance and 8.3% end of the year allowance.
  • An extensive package of fringe benefits (e.g. excellent technical infrastructure, on-campus child care, and excellent sports facilities).

Information and application

For any further inquiries on the content of the position, please contact Joaquin Vanschoren (j.vanschoren[at]tue.nl).
About the employment conditions you may contact the HR advisor, Mrs. Arianne Boekemea (pzwin[at]tue.nl)

If you would like to apply, please send us your application by using the 'apply for this job'-button at the top of this page (applications via e-mail will not be accepted).

You can upload only 5 documents up to 2 MB each. If necessary please combine documents. 

The application should consist of the following parts:

  • Cover letter explaining your motivation and qualifications for the position;
  • Detailed Curriculum Vitae;
  • List of publications