Research Assistant - Machine Learning

Technical University of Denmark - Department of Management Engineering

The Machine Learning for Mobility group (MLM) of the Technical University of Denmark (DTU), Department of Management Engineering, is looking for excellent applicants to initiate research in the group, starting as soon as possible.

We do methodological research in Statistics and Machine Learning, with particular focus on Transportation problems. Given the complexity of our cities and transportation systems, we believe we need both a strong methodological background as well as deep domain knowledge to have true impact in the real-world. Thus, we always aim to contribute to both research communities of Machine Learning and Transportation. It is an ambitious, yet very exciting place to be!

The research in our group

A strategic research direction in our group has focused on pure methodological research in Machine Learning, where we aim to develop new tools for a wider range of applications, and contribute to scientific development in ML (e.g. we have published in ICML, IEEE-TPAMI, AAAI, HCOMP). This project will belong to this direction, particularly on the intersection between Bayesian models and Deep Learning, within our new research project, on Correlated Model Networks (CMN) and transfer learning.

Responsibilities and tasks

The research assistant will join a team of researchers, focused on the problem of Transfer Learning. This is particularly relevant in problems where spatial and/or temporal correlations are prevalent. We believe that, in near future, we will have multiple models, of different forms, running in parallel, and “collaborating” towards varied goals. In this sense, it becomes important to design tools to support models like Deep Learning Networks, Linear Regression, Probabilistic Graphical Models, and so on, to “speak” with each other.

The objective is thus to join a group in advancement of current and future paradigms for more resilient Machine Learning methods, through transfer learning.


  • A Masters degree in computer science, statistical physics, or equivalent.
  • Excellent programming capabilities, in at least one scientific language (e.g. Python, Matlab, R, Julia).
  • Excellent background in statistics and probabilities.

The following soft skills are also important:

  • Curiosity and interest about current and future mobility challenges (e.g. autonomous mobility, traffic prediction, travel behaviour).
  • Good communication skills in English, both written and orally.
  • Willingness to engage in group-work with a multi-national team.

Application procedure

To apply, please read the full job advertisement at

Application deadline: 5 March 2018.

The Machine Learning for Mobility group belongs to the Transport Modeling division of the department of Management Engineering at DTU. The division conducts research and teaching in the field of traffic and transport planning, with particular focus on behavior modeling, machine learning, and simulation.

DTU is a technical university providing internationally leading research, education, innovation, and scientific advice. Our staff of 5,800 advance science and technology to create innovative solutions that meet the demands of society; and our 11,000 students are being educated to address the technological challenges of the future. DTU is an independent academic university collaborating globally with business, industry, government, and public agencies.

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