Doctoral Student in Scalable Probabilistic Machine Learning and Compilers

3 days ago


Stockholm, Stockholm, Sweden Karlstad University Full time

Doctoral Student in Scalable Probabilistic Machine Learning and Compilers

Since its founding in 1827, KTH Royal Institute of Technology in Stockholm has grown to become one of Europe's leading technical and engineering universities. The doctoral student position focuses on fundamental research combining probabilistic machine learning and compilers. Specifically, research challenges concern methods for finding compilation techniques and novel probabilistic machine-learning methods that scale up to very large problems, particularly in the context of phylogenetic applications. The focus is on Bayesian inference techniques and designing probabilistic programming languages for usability and performance. Exploring combinations with other machine learning and generative AI methods is also encouraged.

What we offer
  • A dynamic and international research environment in collaboration with industries and prominent universities worldwide.
  • Employee benefits and a monthly salary according to KTH's Doctoral student salary agreement.
  • A supportive institution in matters of working conditions, gender equality, and diversity.
  • Work and study in Stockholm, close to nature and water.
  • Help to relocate and settle in Sweden and at KTH.
Admission requirements

To be admitted to postgraduate education, the applicant must have basic eligibility in accordance with either of the following:

  • Passed a second cycle degree (e.g., master's degree), or
  • Completed course requirements of at least 240 higher education credits, including at least 60 second-cycle higher education credits, or
  • Acquired equivalent knowledge in some other way.

Additionally, a mandatory requirement for English equivalent to English B/6 is required.

Selection

Successful candidates need to be goal-oriented and persevering. During the selection process, candidates will be assessed on their ability to:

  • Independently pursue their work
  • Collaborate with others
  • Maintain a professional approach
  • Analyze and work with complex issues

Excellent knowledge of computer science, particularly in machine learning, compilers, algorithms, or programming language theory, is required. Great emphasis will be placed on personal skills.

Application process

Apply for the position through KTH's recruitment system. Ensure that the application is complete according to the advertisement's instructions. Applications must be received by the closing date at midnight, CET/CEST.

Applications must include:

  • CV detailing relevant professional experience and knowledge.
  • Application letter explaining your motivation for pursuing research studies (maximum 2 pages).
  • Copies of diplomas and grades from previous studies and certificates of language requirements. Translations into English or Swedish if necessary.
  • Representative publications or technical reports with summaries and links for longer documents.
Other information

KTH is committed to gender equality, diversity, and equal conditions as part of its core values. A position at KTH may be classified as security-sensitive under the Protective Security Act (2018:585), requiring a security clearance with the applicant's consent.

About KTH

KTH Royal Institute of Technology is Sweden's largest technical research and learning institution, home to students, researchers, and faculty from around the world. Our research and education cover a wide area including natural sciences and all branches of engineering, as well as architecture, industrial management, urban planning, history, and philosophy.

Type of employment: Temporary position
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: 1
Full-time equivalent: 100%
City: Stockholm
County: Stockholms län
Country: Sweden
Reference number: PA-2025-0402
Contact:

  • Professor David Broman, dbro@kth.se
  • Lisa Olsson HR Officer, rekrytering@eecs.kth.se
Published: 2025-02-13
Last application date: 2025-03-24
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