Research Assistant on Machine Learning research

DTU Management Engineering
Monday 05 Feb 18

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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.

Qualifications 

  • 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
Assessment 
The assessment of the applicants will be made by 31 March 2018.

We offer
DTU is a leading technical university globally recognized for the excellence of its research, education, innovation and scientific advice. We offer a rewarding and challenging job in an international environment. We strive for academic excellence in an environment characterized by collegial respect and an academic freedom tempered by responsibility.

Salary and appointment terms
The appointment will be based on the collective agreement with the Confederation of Professional Associations. The allowance will be agreed with the relevant union. The period of employment is 6 months.

You can read more about career paths at DTU here.  

Further information
Further information may be obtained from Francisco Pereira, tel: +45 4525 1496.

You can read more about DTU Management Engineering on www.man.dtu.dk.  

Application procedure
Please submit your online application no later than 5 March 2018. Applications must be submitted as one PDF file containing all materials to be given consideration. To apply, please open the link "Apply online", fill in the online application form, and attach all your materials in English in one PDF file. The file must include: 
  • Application (cover letter)
  • CV
  • Diploma (MSc)
Applications and enclosures received after the deadline will not be considered.

All interested candidates irrespective of age, gender, disability, race, religion or ethnic background are encouraged to apply.

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 Management Engineering contributes actively to the development of management tools and optimisation of processes by using and re-thinking theoretical engineering perspectives, models and methods. Through our research and teaching, we ensure an innovative, competitive and sustainable organisation and use of technologies within areas such as energy and climate, transportation, production and health, both domestic and abroad. DTU Management Engineering has 340 employees; including an academic staff of 190 and 68 PhD students. More than 20 % of our employees are from abroad and in all 38 different nationalities are represented at the Department.

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.