Postdoctoral Researcher in Machine Learning

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Do you want to work with modern machine learning methods supported by competent colleagues in a leading international environment? Do you want an employer that invests in sustainable employee relations and offers secure, favorable working conditions? Welcome to apply for a postdoctoral position at Uppsala University. Uppsala University has a long tradition of successful research – among its alumni are 16 Nobel Prize laureates, most recently Svante Pääbo. The University is unique in combining IT with broader research, from life sciences to humanities. The Department of Information Technology holds a leading position in both research and education at all levels. Today it is Uppsala University's third largest department with just over 350 employees, of which 120 are teachers and 120 are doctoral students. Approximately 5,000 undergraduate students take one or more courses at the department each year. More information about us can be found on the Department of Information Technology's website. At the Division of Systems and Control, we develop both theory and concrete tools for designing systems that learn, reason, and act in the real world based on a seamless combination of data, mathematical models, and algorithms. Our research integrates expertise from machine learning, optimization, control theory, and applied mathematics, spanning various application areas such as medicine, energy systems, biomedical systems, neuroscience, and security. The division has an extensive network of long-standing international collaborators worldwide, for example at University of Cambridge, University of Oxford, Imperial College London, University of Sydney, University of Newcastle, and Aalto University. Work Duties Research on fundamental models and methods in machine learning and their applications in medicine. We will continue our work on extracting knowledge from large-scale ECG datasets and possibly related data. The aim is to investigate the use of these models for decision support, and the position may also involve work with decision algorithms. The postdoctoral researcher will collaborate with colleagues at the Faculty of Medicine here in Uppsala and likely also with our collaborators in Brazil. Key technical terms for the position include: probabilistic models, deep learning, decision algorithms, Bayesian inference, and precision medicine. The position may include teaching up to 20% depending on availability and interest. Qualification Requirements PhD in machine learning, control theory, signal processing, computational statistics, or a related relevant field, or a foreign degree deemed equivalent to a Swedish PhD in machine learning, control theory, signal processing, or computational statistics. The degree must be completed by the time the employment decision is made. Primarily, candidates who have completed their degree within the last three years should apply. In calculating the three-year timeframe, the start date is the last application deadline. If there are special circumstances, such a degree may have been completed earlier. Special circumstances include leave due to illness, parental leave, positions of trust within labor organizations, etc. We are looking for candidates with: a strong interest in and experience developing new methods in machine learning, ability to apply deep learning to large datasets, ability to communicate technical material effectively in spoken and written form (English), good practical programming skills (preferably in Python). personal qualities such as a high level of creativity, attention to detail, and/or a structured approach to problem-solving are essential. Publications at leading machine learning conferences are a significant plus. You are expected to be able to teach in Swedish or English. Additional Desired/Meritorious Qualifications Experience in interdisciplinary research is valuable. As a person, you are creative, detail-oriented, and have a structured approach. In the selection process, we will assess your ability to independently drive your work forward, to collaborate with others, to maintain a professional attitude, and to analyze and work with complex problems. Great emphasis will be placed on personal qualities and personal suitability. The application should contain: A curriculum vitae (CV), A publication list, A description of your current and previous research (max 1 page) and proposal for future research (max 1 page), Contact information for two references. About the Employment The employment is time-limited for 2 years according to central collective agreement. The position is full-time. Start date: October 1, 2026, or by agreement. Location: Uppsala. Information about the employment is provided by: Professor Thomas Schön, 018 - 471 25 94, [email protected] In this recruitment, we have replaced the personal letter with questions that you answer in connection with your application. The answers will be used as part of the selection process. Welcome to submit your application by August 28, 2026, UFV-PA 2026/2006. Uppsala University is a broad research university with a strong international position. The ultimate goal is to conduct education and research of the highest quality and relevance in order to make a difference in society. Our most important asset is all 7,500 employees and 53,000 students who, with curiosity and engagement, make Uppsala University one of the country's most exciting workplaces. Read more about our benefits and what it is like to work at Uppsala University: https://uu.se/om-uu/jobba-hos-oss/ The employment may be subject to security vetting. Security vetting is a requirement for employment; applicants must be approved. We decline offers of recruitment and advertising assistance. Applications are received through Uppsala University's recruitment system. Labor representatives: Saco-S - [email protected], Seko - [email protected], ST (OFR/S) - [email protected]

Přehled

Typ

job

Stav

active

Viditelnost

public

Město

Uppsala

Adresa

box 256

GPS

59.8710738, 17.5946002kopírovatotevřít v ▾

Email

[email protected]

Telefon

018 - 471 25 94

Zobrazení

2

Publikováno

10. 6. 2026

Upraveno

21. 6. 2026

Parametry