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Third-cycle subject: Applied and computational mathematics
The Department of Mathematics at KTH is looking for candidates for two PhD positions specializing in mathematical statistics. The research area lies at the intersection of probability, computational statistics, machine learning and AI. One of the projects is funded the Swedish e-Science Research Centre (SeRC).
A wide range of applications in data science are based on large-scale statistical computations. These computations can be made efficient by well-designed algorithms suitable for parallel computing. In one of the projects, we will explore statistical learning algorithms from a mathematical perspective, using techniques from large deviations theory to quantify convergence properties of the algorithms. In the second project we will study how deep neural networks and other deep function approximations may be used to design efficient statistical computational methods. The projects are suitable for students interested in topics and methods such as large deviations theory, statistical learning, Bayesian statistics, Monte-Carlo methods, and deep learning.
Supervision: Professor Henrik Hult and Professor Jimmy Olsson is proposed to supervise the doctoral student. Decisions are made on admission.
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:
Special admission requirements for the doctoral program requires that the applicant's second-cycle education has a focus on mathematics, applied mathematics or computational mathematics in a broad sense.
In addition to the above, there is also a mandatory requirement for English equivalent to English B/6, read more here
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:
After the qualification requirements, great emphasis will be placed on personal competency.
Target degree: Doctoral degree
Only those admitted to postgraduate education may be employed as a doctoral student. 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 may be renewed for a maximum of two years at a time. In the case of studies that are to be completed with a licentiate degree, the total period of employment may not be longer than what corresponds to full-time doctoral education for two years.
You will find contact information for union representatives on KTH's website.
You will find contact information for doctoral section on the section's website.
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:
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 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.
Type of employment | Temporary position |
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Contract type | Full time |
First day of employment | According to agreement |
Salary | Monthly salary according to KTH's doctoral student salary agreement |
Number of positions | 2 |
Full-time equivalent | 100% |
City | Stockholm |
County | Stockholms län |
Country | Sweden |
Reference number | S-2023-0935 |
Contact |
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Published | 08.Jun.2023 |
Last application date | 23.Jun.2023 11:59 PM CEST |