PhD scholarships (3) in Machine Learning Metamodeling Architectures for Scientific Simulation - DTU Management

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Kongens Lyngby

We offer 3 PhD positions in the A rtificial Intelligence for P olicy Ex cellence in the Climate Crisis (APEX) project at the Technical University of Denmark, focused on developing a Machine Learning approximations for simulators (also known as ML metamodels). Such approximations have the potential of vastly accelerating simulation studies, and supporting applications in many important contexts, including transport, energy, environment, material science, physics and any other domain where scientific simulation is important.

More often than not, simulation tools are extremely complex and slow to run. If we also consider that they may have many parameters and input data (with uncertainty) to consider, we quickly arrive to the conclusion that most of the times, we can only access a tiny portion of their true potential. This dilemma affects our lives in many ways. In particular, for policy decision making (e.g. transport policy), it prevents us from exhaustively searching for the best parameters (e.g. how much should a vehicle tax be? Should we build a new bridge/metro/road? What should the bus ticket price be?).

The goal of these 3 PhDs is to develop different types of machine learning-based approximations to simulation tools, that can accelerate their runtimes by many orders of magnitude. If this happens with good accuracy in- and out-of-distribution, then we can eventually apply them directly in such policy studies.

The 3 PhDs are collaborative yet independent, because they explore methodological concepts in three groups:

  • Active Learning and Causal Discovery
  • Graph Neural Networks and Neural Architecture Search
  • Polynomial Neural Networks and Physics-informed deep learning

Under the supervision of Professor Francisco Pereira, together with 3 colleagues (Associate Professors Filipe Rodrigues and Carlos Azevedo, Assistant Professor Guido Cantelmo), this will be an exciting project, that will become the foundation for very promising future avenues in AI and Science. The applicability of such a methodology has vast implications for a number of fields beyond transport and climate. Essentially, any application area where scientific simulation is important will benefit from it.

The project is entirely funded under the Novo Nordisk Data Science Distinguished Investigator program .

You will be a member of the ITS section of the Transport division at the Department for Technology, Management and Economics (DTU Management) at the Technical University of Denmark (DTU).

Responsibilities and qualifications
Your primary tasks will be to:

  • Become familiar with advanced concepts and existing literature in ML metamodeling
  • Become familiar with the simulation tools used in the APEX project, supported by the remaining team
  • Become familiar with advanced concepts on the specific ML methodology of your PhD project
  • Create ground-truth datasets for training, validation and test of the methodology
  • Implement and test the new methodology of your PhD project
  • Co-advise masters students involved in the project whenever appropriate, regularly meet with PIs, and disseminate new findings in journals/conferences.

You must have a two-year master's degree (120 ECTS points) in Computer Science, Informatics Engineering, Mathematical Modeling, Transport Modeling or equivalent, or a similar degree with an academic level equivalent to a two-year master's degree.

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 DTU's rules for the PhD education .

Assessment
The assessment of the applicants will be made by 10 June 2024.

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.

You can read more about career paths at DTU here http://www.dtu.dk/english/about/job-and-career/working-at-dtu/career-paths.

Further information
Further information about the position may be obtained from Professor Francisco Pereira ([email protected] ).

You can read more about DTU Management at www.man.dtu.dk/english.

If you are applying from abroad, you may find useful information on working in Denmark and at DTU at DTU – Moving to Denmark . Furthermore, you have the option of joining our monthly free seminar “PhD relocation to Denmark and startup “Zoom” seminar ” for all questions regarding the practical matters of moving to Denmark and working as a PhD at DTU.

Application procedure
Your complete online application must be submitted no later than 10 March 2024 (23:59 Danish time) . Applications must be submitted as one PDF file containing all materials to be given consideration. To apply, please open the link "Apply now", 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 including 3 reference contacts)
  • Curriculum vitae
  • Grade transcripts and BSc/MSc diploma (in English) including official description of grading scale

You may apply prior to ob­tai­ning your master's degree but cannot begin before having received it.

Applications received after the deadline will not be considered.

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

The ITS section belongs to the Transport Science division of the Department of Technology, Management and Economics (DTU Management) at DTU. The division conducts research and teaching in the field of traffic and transport planning, with particular focus on behavior modelling, machine learning and simulation.

About us
DTU Management conducts excellent research at the intersection of management, technology and economics. We develop solutions in close cooperation with companies and public authorities. Our research aims to strengthen welfare, productivity and sustainability within society. A key element is technology’s role and its interaction with industry and individuals. The department offers a wide range of courses and programmes at the bachelor’s, master’s and PhD levels across DTU’s study programmes. The department has 200+ employees, with approximately 50% coming from abroad.

Technology for people
DTU develops technology for people. With our international elite research and study programmes, we are helping to create a better world and to solve the global challenges formulated in the UN’s 17 Sustainable Development Goals. Hans Christian Ørsted founded DTU in 1829 with a clear mission to develop and create value using science and engineering to benefit society. That mission lives on today. DTU has 13,500 students and 6,000 employees. We work in an international atmosphere and have an inclusive, evolving, and informal working environment. DTU has campuses in all parts of Denmark and in Greenland, and we collaborate with the best universities around the world.

Kilde: Jobnet.dk


Information og data

Denne ledige stilling har jobtypen "Øvrige", og befinder sig i kategorien "Øvrige stillinger".

Arbejdsstedet er beliggende i Kongens Lyngby.

Jobbet er oprettet på vores service den 8.2.2024, men kan have været deaktiveret og genaktiveret igen.

Dagligt opdateret: Dette job opdateres dagligt ud fra jobudbyderens hjemmeside via vores søgemaskineteknologi og er aktivt lige nu.
  • Øvrige
  • Kongens Lyngby
  • Søndag den 10. marts 2024

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