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Postdoc in Machine Learning for Road Condition Prediction at Technical University of Denmark (Copenhagen, Denmark)

The Section of Cognitive Systems (COGSYS) at DTU Compute is looking for a post doc within the area of machine learning and signal processing. The starting date is 1 October or as soon as possible thereafter. The position is part of the LiRA (Live Road Assessment) project funded by the Innovation Fund Denmark.

The Section for Cognitive Systems is a lively and research oriented group of scientists and support staff with a shared interest in information processing I an man and in computers, and a particular focus on the signals they exchange - audio, imagery, behavior.

DTU Compute is an internationally unique academic environment spanning the science disciplines mathematics, statistics and computer science. At the same time, we are an engineering department covering informatics and communication technologies (ICT) in their broadest sense. Finally, we play a major role in addressing the societal challenges of the digital society where ICT is a part of every industry, service, and human endeavor.

DTU Compute strives to achieve research excellence in its basic science disciplines, to achieve technological leadership in research and innovation, and to address societal challenges in collaboration with partners at DTU and other academic institutions, nationally and internationally, and, equally important, with industry and organisations. We communicate and collaborate with leading centers and strategic partners in order to increase participation in major consortia.

DTU Compute plays a central role in education at all levels of the engineering programmes at DTU - both in terms of our scientific disciplines and our didactic innovation.

The objective of the LiRA project is to build a system that collects data from the sensors of a fleet of cars and using these data for deriving the state of the roads pavements, so that road pavement surveys can be obtained in a cheaper and more timely way.

Responsibilities and tasks
As a post doc, you will be responsible for analysing the car fleet data and develop methods for modelling car sensor responses. The model to be developed is a hybrid model consisting of two parts; a predictive machine learning model and a physical model. DTU Civil Engineering will develop the physical model so the hybrid model will be research endeavor in close collaboration with DTU Civil engineering as well as the other partners in the project.

The goal is to establish the main features of the car signals and best build a predictive model that maps the car data to road conditions. We will have access to road condition data provided by Danish Road Department (the PI of the LiRA project) to create such model, as well as car sensor data provided by the industry partner Green Mobility.

As our new post doc, as part of this team, you will be responsible for:

  • developing machine learning models for mapping car sensor data to road condition estimation
  • lead the research on the interplay of machine learning models and phyiscal models
  • testing and comparing different approaches in real-world settings and take part in designing the data collection process
  • identify individual baselines
  • estimating the reliability of the models and resulting classifications
  • lead the publication of academic papers in high-impact peer-reviewed journals or conferences

The role includes collaboration with other members of the team, both at DTU Compute, DTU Civil Engineering and our industrial- and research partners.

Qualifications
Candidates should have a PhD degree or equivalent. The PhD degree can be in machine learning or related fields. We are looking for candidates that preferably have a good research track record working in one or more of the following research areas: 

  • machine learning and deep learning
  • mathematical modelling and computing
  • signal processing
  • cloud computing

In addition, you:

  • have a strong mathematical foundation
  • have strong analytical and academic skills
  • enjoy working with complex topics
  • are driven by pushing boundaries and can generate and carry out new ideas, building on previous scientific work yet still covering new ground
  • have compelling communication skills in English, with a track record of scientific publications, conference presentations, reports and/or popular dissemination
  • have the ability and drive to work cross-disciplinarily in an international academic and industrial research setting

We offer
DTU is a leading technical university globally recognised 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 characterised by collegial respect and academic freedom tempered by responsibility.

Salary and terms of employment
The appointment will be based on the collective agreement with the Danish Confederation of Professional Associations. The allowance will be agreed upon with the relevant union. The period of employment is one year. The position is a full-time position.

The workplace is primarily at DTU Lyngby Campus but can also involve work at our industrial research partners.

You can read more about career paths at DTU here.

Further information
Further information may be obtained from Tommy Sonne Alstrøm, tel.: +45 4525 3431.

You can read more about DTU Compute and COGSYS at www.compute.dtu.dk.

Application procedure
Please submit your online application no later than 9 September 2019 (23:59 local time). 

Apply online at www.career.dtu.dk.

Applications must be submitted as one PDF file containing all materials to be given consideration. To apply, please open the link "Apply online", fill out 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/PhD)
  • List of publications

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.