Doctoral student in probability theory
20 hours ago
The University of Gothenburg tackles society’s challenges with diverse knowledge. 56,000 students and 6,600 employees make the university a large and inspiring place to work and study. Strong research and attractive study programmes attract researchers and students from around the world. With new knowledge and new perspectives, the University contributes to a better future.
The Department of Mathematical Sciences at Chalmers University of Technology and the University of Gothenburg has about 200 employees and is the largest department of mathematics in Sweden. The department has three scientific divisions: Algebra and Geometry, Analysis and Probability Theory, and Applied Mathematics and Statistics, and conducts successful research in pure and applied mathematics and mathematical statistics in a wide range of research areas. We have an international environment with frequent exchanges with other universities around the world. The department provides a friendly, creative, and supportive atmosphere with a steady flow of international guests. There are many committed teachers with extensive and broad experience of all aspects of higher education. More information about us can be found on our website: http://www.chalmers.se/math/
At the division of Applied Mathematics and Statistics, we conduct research within probability theory and its applications, the theory and implementation of finite element methods, inverse wave propagation problems, stochastic partial differential equations, geometric numerical integration, optimization, biomathematics, biostatistics, spatial modeling, Bayesian inference, high-dimensional data, large-scale computational methods, and bioinformatics. The division is also expanding in the area of data science and machine learning.
We are looking for a doctoral student in probability theory, broadly interpreted, to work under the supervision of Associate Professor Pierre Nyquist.
Our department continuously strives to be an attractive employer. Equality and diversity are substantial foundations in all our activities. We work actively to be a parent-friendly organization.
General information about being a doctoral student at the University of Gothenburg can be found on the university's doctoral student pages.
Position Overview
We will recruit one doctoral student in probability theory, broadly interpreted, to work under the supervision of Associate Professor Pierre Nyquist. The direction of the project will be determined together with the incoming student. Potential topics include but are not limited to: large deviation theory; high-dimensional probability; theory of Markov processes; Monte Carlo methods, particularly Markov chain Monte Carlo; stochastic optimisation; optimisation over random structures; computational hardness; metastability; gradient flows; stochastic optimal control. An overall theme of interest is questions in probability theory and analysis related to sampling, optimisation, and learning problems in high dimensions.
Students with a strong background in mathematics in general, and an interest in topics related to probability and analysis, are encouraged to apply. There are no formal requirements about previous experience in specific areas; if you have questions about how your background and interests might fit, you are welcome to reach out via email. Candidates from historically underrepresented groups are especially encouraged to apply.
The employment is a fixed-term position limited to a maximum of five years, four years of studies and up to one year of departmental work distributed during the whole employment period.
Minimum Qualifications
The eligibility for academic positions is given in the Swedish Higher Education Ordinance. To qualify for the position, the applicant must have obtained a master’s degree or a 4-year bachelor’s degree in mathematics, applied mathematics, mathematical statistics, computer science, physics, or other relevant field, or expect to complete such a degree prior to the start of the employment.
Good presentation and communication skills in oral and written English are required.
Experience in one or several of the following areas may be meritorious: (measure-theoretic) probability, stochastic processes, stochastic analysis, partial differential equations, functional analysis.
Please include all relevant work such as bachelor's or master's thesis and articles (provide an English summary if necessary) that you have authored or co-authored.
Application Process
You can apply to be admitted to doctoral education via the University of Gothenburg’s recruitment portal. It is your responsibility to ensure that the application is complete as per this notice and that the University receives it by the final application deadline.
Applications must be received by: 2025-02-19
Contact Information
Pierre Nyquist, Professor, Applied Mathematics and Statistics, +46 31 772 2294, pnyquist@chalmers.se
Irina Pettersson, Docent, Head of Unit of Applied Mathematics and Statistics, +46 31 772 , irinap@chalmers.se
Required Application Documents
- Application letter (max 2 pages) detailing your academic interests, previous studies, scientific work experience, research interests, and interest in this specific position.
- Detailed curriculum vitae.
- Electronic copies of your master and bachelor transcripts.
- Copies of your bachelor’s and master’s thesis if available.
- Desirable but not mandatory: Contact information for up to two references.
Information for International Applicants
Choosing a career in a foreign country is a big step. Thus, to give you a general idea of what we and Gothenburg have to offer in terms of benefits and life in general for you and your family/spouse/partner, please visit:
The University works actively to achieve a working environment with equal conditions and values the qualities that diversity brings to its operations.
Published
2024-12-18
2025-02-19 23:59 (Europe/Stockholm)
2025-02-19 23:59 (CET)
The University of Gothenburg (Göteborgs Universitet) is environmentally certified and works actively for sustainable development.
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