Uppsala University invites applications for a PhD position focusing on sequential decision-making in machine learning. This position offers an opportunity to work in a dynamic, international environment with support from experienced colleagues. Funded by the Wallenberg AI, Autonomous Systems and Software Program (WASP), this project aims to develop theory and methods for adaptive decision-making based on real-time data collection. The successful candidate will contribute to interdisciplinary research in collaboration with leading institutions worldwide.
The PhD project will focus on advancing theory and methods for sequential decision-making in various applications, such as adaptive experiment design and resource management. The candidate will collaborate with supervisors and international partners to address real-world challenges in industries, utilities, and healthcare. The position offers opportunities for interdisciplinary research, professional development, and international networking within the framework of WASP.
Qualifications 
•    Master’s degree (second-cycle) in engineering physics, electrical engineering, applied mathematics, mathematical statistics, or related field
•    Strong background in statistical learning and proficiency in programming (Python, Julia, or Matlab)
•    Excellent communication skills in English, both written and oral
•    High academic performance and creativity in problem-solving
•    Prior coursework or experience in machine learning, optimization, signal processing, or control theory is advantageous
How to Apply: 
Interested candidates should submit the following documents by email to the specified contacts:
1.    Statement of motivation (up to 2 pages) explaining the applicant’s interest and suitability for the position
2.    Curriculum Vitae (CV)
3.    Transcripts of records with grades (translated to English or Swedish)
4.    Master’s thesis or draft, publications, and other relevant documents
5.    Contact information for references, including up to two letters of recommendation Applicants should indicate their earliest possible starting date of employment.