id: NDg5MDAxNiA3

reference: 4890016

documentId: 4890016

connectionPointId: 7

lastModificationDate: 1539163685183

stillingsbetegnelse:
PhD Scholarship in Machine Learning and Demand Modeling

jobbeskrivelse:

The Machine Learning for Mobility (MLM) and the Demand Modeling (DM) groups of the Technical University of Denmark (DTU), Department of Management Engineering, are looking for excellent applicants to pursue PhD studies in a joint research project, starting in August 2017.

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!

A strategic research direction in our group focuses on applying cutting edge methodological research from Machine Learning into Transport Demand models. This PhD will belong to this direction, particularly on the intersection between Deep Learning and population synthesis.

Responsibilities and tasks

The focus of this project is on developing generative models (Generative Adversarial, Variational Autoencoders, Exponential families, Restricted Boltzmann machines, etc.) that are able to learn multiple dimensional population characteristics across space and time.

We believe that, in near future, we will have a combination of Machine Learning, Simulation and 'classical' Choice modelling, as the state-of-the-art of Transport Modeling in General.

The objective is thus to advance the current and future paradigms for more scalable and accurate methods, through transfer learning. Since the PhD is not restricted to a single option in Machine Learning, reasonable proficiency in its statistical and probability foundations is important.

Qualifications

• A Masters degree in computer science, computer engineering, statistical physics, econometrics, or related
• 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

Approval and Enrolment

The scholarship for the PhD degree is subject to academic approval, and the candidate will be enrolled in one of the general degree programmes at DTU. For information about our enrolment requirements and the general planning of the PhD study programme, please see the DTU PhD Guide. http://www.dtu.dk/english/Education/PhD/Rules/PhDguide

Assessment

The assessment of the applicants will be made by 25 October 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 academic freedom tempered by responsibility.

Salary and appointment terms

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 3 years.

The workplace will be DTU Lyngby Campus.

Further information For more information, please contact Francisco C. Pereira, camara (at) dtu.dk or Jeppe Rich, rich (at) dtu.dk.

You can read more about DTU Management Engineering on http://www.man.dtu.dk/english.

Application Please submit your online application no later than 24 October 2018 (local time). 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:

• A letter motivating the application (cover letter)
• Curriculum vitae
• Grade transcripts and BSc/MSc diploma
• Excel sheet with translation of grades to the Danish grading system (see guidelines and Excel spreadsheet here) http://www.dtu.dk/english/Education/phd/Applicant/Pre_acceptance-1-

Candidates may apply prior to ob­tai­ning their master's degree, but cannot begin before having received it.

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

DTU Management Engineering contributes actively to the development of management tools and optimization 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 organization and use of technologies within areas such as energy and climate, transportation, production and health, both domestic and abroad. DTU Management Engineering has 350 employees, including around 70 PhD students. More than 20% of our employees are from abroad and a total of 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 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 academic university collaborating globally with business, industry, government and public agencies.


numberOfPosts: 1

jobCategoriesCodes_0: http://data.europa.eu/esco/isco/C2310

abstractJV_contact_0: Please apply using one of the specified channels

positionTypeCode: directhire

contractTypeCodes_0: fulltime

Arbejdsgiver Navn: Danmarks Tekniske Universitet

source: DK-STAR