Postdoc in Machine Learning for Road Condition Prediction

A new opening postdoctoral associate position in civil engineering is available at Technical University of Denmark, Denmark. Potential candidates should apply before September 09, 2019.

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

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

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 endeavour.

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 centres 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.

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 endeavour 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.

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

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

DTU Compute has a total staff of 400 including 100 faculty members and 130 PhD students. We offer introductory courses in mathematics, statistics, and computer science to all engineering programmes at DTU and specialised courses to the mathematics, computer science, and other programmes. We offer continuing education courses and scientific advice within our research disciplines, and provide a portfolio of innovation activities for students and employees. DTU is a technical university providing internationally leading research, education, innovation and scientific advice. Our staff of 6,000 advance science and technology to create innovative solutions that meet the demands of society, and our 11,200 students are being educated to address the technological challenges of the future. DTU is an independent university collaborating globally with business, industry, government and public agencies.


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