Doctoral student in Deep Generative Models for Reconstruction from Sparse Measurements

Royal lnstitute of Technology
November 16, 2022
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Working Time:Full time
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Project description

Third-cycle subject: Computer Science

This project involves the reconstruction of 3-dimensional temporal fields from sparse measurements using deep generative models (DGM). The students will work on core machine learning problems such as DGMs and specifically develop (1) joint optimization of sensor locations and field reconstruction, and (2) loss functions suitable for downstream prediction tasks. Examples of techniques include DGMs such as VAE, differentiable optimization of discrete variables such as Gumbel distribution and recent architectures such as vision transformers.

On the application side, in collaboration with the engineering mechanics department, we use the developed techniques to model flow in simulated or real urban environments from sparse measurements

Supervision: Hossein Azizpour and Ricardo Vinuesa are proposed to supervise the doctoral student. Decisions are made on admission.

What we offer
  • The possibility to study in a dynamic and international research environment in collaboration with industries and prominent universities from all over the world. Read more
  • A workplace with many employee benefits and monthly salary according to KTH's Doctoral student salary agreement.
  • Postgraduate education at an institution that is active and supportive in matters pertaining to working conditions, gender equality and diversity as well as the study environment.
  • Work and study in Stockholm, close to nature and the water.
  • Help to relocate and be settled in Sweden and at KTH.
  • Access to a research environment with both fundamental deep learning and multidisciplinary research
  • Access to state-of-the-art GPU resources for deep learning research
  • Financial support for the presentation of own's and collaborative works at international venues.
  • Admission requirements

    To be admitted to postgraduate education (Chapter 7, 39 § Swedish Higher Education Ordinance), the applicant must have basic eligibility in accordance with either of the following:

  • passed a second cycle degree (for example a master's degree), or
  • completed course requirements of at least 240 higher education credits, of which at least 60 second-cycle higher education credits, or
  • acquired, in some other way within or outside the country, substantially equivalent knowledge
  • One of the recruitments funded by the EU Doctoral Network must comply with the following mobility rule: they must not have resided or carried out their main activity (work, studies, etc.) in Sweden for more than 12 months in the 36 months immediately before their recruitment date. This requirement does not apply to the second doctoral student position.
  • In addition to the above, there is also a mandatory requirement for English equivalent to English B/6, read more here

    Selection

    In order to succeed as a doctoral student at KTH, you need to be goal oriented and persevering in your work. During the selection process, candidates will be assessed upon their ability to:

  • independently pursue his or her work
  • collaborate with others,
  • have a professional approach and
  • analyse and work with complex issues.
  • Candidates should also have:

  • experience and education in both theory and practice of machine learning, especially deep learning and
  • prior experience with remote GPU and HPC services.
  • After the qualification requirements, great emphasis will be placed on personal competency.

    Target degree: Doctoral degree Information regarding admission and employment

    Only those admitted to postgraduate education may be employed as doctoral students. The total length of employment may not be longer than what corresponds to full-time doctoral education in four years ' time. An employed doctoral student can, to a limited extent (maximum 20%), perform certain tasks within their role, e.g. training and administration. A new position as a doctoral student is for a maximum of one year, and then the employment contract may be renewed for a maximum of two years at a time.

    Union representatives

    You will find contact information for union representatives on KTH's website.

    Doctoral section (Students' union on KTH Royal Institute of

    Technology)

    You will find contact information for the doctoral section on the section's website.

    Application

    Apply for the position and admission through KTH's recruitment system. It is the applicant's responsibility to ensure that the application is complete in accordance with the instructions in the advertisement.

    Applications must be received at the last closing date at midnight, CET/CEST (Central European Time/Central European Summer Time).

    Applications must include the following elements:

  • CV including your relevant professional experience and knowledge.
  • Application letter with a brief description of why you want to pursue research studies, what your academic interests are and how they relate to your previous studies and future goals. (Maximum 2 pages long)
  • Copies of diplomas and grades from previous university studies and certificates of fulfilled language requirements (see above). Translations into English or Swedish if the original document is not issued in one of these languages. Copies of originals must be certified.
  • Representative publications or technical reports. For longer documents, please provide a summary (abstract) and a web link to the full text.
  • Other information

    Striving towards gender equality, diversity and equal conditions is both a question of quality for KTH and a given part of our values.

    For information about the processing of personal data in the recruitment process please read here.

    We firmly decline all contact with staffing and recruitment agencies and job ad salespersons.

    Disclaimer: In case of discrepancy between the Swedish original and the English translation of the job announcement, the Swedish version takes precedence.

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