The Department of Information Technology at Uppsala University is inviting applications for three PhD positions in Machine learning.
About the Project:
- The research projects for these positions will be within the areas of machine learning, including the development and analysis of models or computational learning methods or reinforcement learning.
- The three problem formulations that are most relevant for this opening are the following:
- Machine learning methods for causal inference and analysis: Modern machine learning (ML) methods are capable of learning accurate predictive models using data from real-world processes.
- Data-driven control and reinforcement learning: The goal of control engineering is to design controllers that make dynamical systems behave in a desired manner. Control theory plays an essential role in a wide range of applications, from simple consumer devices to industrial machines, autonomous vehicles and spacecrafts.
- Developing deep dynamical models: Many real-world systems are dynamical processes. By learning models of such systems we obtain insights about their dynamics, get the capability to predict their behavior under different scenarios, and, in certain instances, control their output.
- Applicant must hold a Master of Science or equivalent in a field that is relevant to the topic of the PhD thesis, good communication skills and excellent study results.
- Applicant must possess sufficient proficiency in oral and written English.
- Experience in machine learning or computational statistics is valued.
Apply online and application should include the following:
- A statement (max. 2 pages) of the applicant’s motivation for applying for this position, including the candidate’s qualifications and research interests and evidence of self-motivation and constructive teamwork.
- Degrees and grades (translated to English or Swedish)
- Master’s thesis (or a draft thereof, and/or some other self-produced technical text), publications, and other relevant documents.
- References with contact information and up to two letters of recommendation may be provided.
|Subject areas||Computer Science, Information Technology|
|Eligibility||Open to all nationalities|
|Deadline||March 27, 2020|