Post-doctoral fellow on automatic machine learning

Post-doctoral fellow on automatic machine learning

Published Deadline Location
30 Jun 30 Aug Eindhoven

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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.

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.

Specifications

Eindhoven University of Technology (TU/e)

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).

Specifications

  • Postdoc
  • Engineering
  • max. 38 hours per week
  • Doctorate
  • V32.4006

Employer

Eindhoven University of Technology (TU/e)

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Location

De Rondom 70, 5612 AP, Eindhoven

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