Up to two PhD student positions in machine learning - Hiring in process/Finished, not possible to apply

The Department of Information Technology has a leading position in research and education. The Department currently has about 280 employees, including 120 teachers and 110 PhD students. More than 4000 students study one or more courses at the department each year. More info: http://www.it.uu.se/?lang=en

The Division of Systems and Control is active in machine learning, automatic control, signal processing, and system identification. The research topic for this position is machine learning,  including the development and analysis of models and/or computational learning methods.

Duties/Project description: 

The exact research topic will be determined in a dialogue between the PhD student and the supervisors starting from the two problem formulations outlined below. Information about our research is available from this popular scientific description http://www.teknat.uu.se/news/nyhetsdetaljsida/?id=9994&area=5,16,17,50&typ=artikel&lang=en and at the group web site: http://www.it.uu.se/research/systems_and_control

The two problem formulations that are relevant for this opening are the following machine learning projects:

1. Statistical machine learning methods for causal inference. In the study of many physical, biomedical and economic processes, the object of interests is the causal influence of certain variables. Consider, for instance, inferring the average effect of a drug on patients or a policy on a population using observational data. Conventional machine learning methods learn associative predictive models of these processes but are often unable to predict outcomes under so-called counterfactual conditions. To overcome these limitations, our aim is to develop new methods that can learn causal models from data from large and heterogeneous populations. The application of such methods is wide and includes medical analysis and policy evaluation.
2. Deep probabilistic programming. This project focuses on the design and development of methods and algorithms that combine deep neural network components (deep learning) and probabilistic programming technology. The research has relevance in application areas where quantification of uncertainty is especially important, such as for example various applications in medicine. The doctoral student will work on topics including models, probabilistic inference algorithms, and possibly optimization. The project will take place in collaboration Prof. David Broman working on programming languages at KTH. There will be a companion PhD student in the project at KTH. This project is funded by the Wallenberg AI, Autonomous Systems and Software Program (WASP). The highest ranked candidates will be nominated to the WASP committee, who takes the final decision if a candidate is funded in the project.
   
   Wallenberg AI, Autonomous Systems and Software Program (WASP) is Sweden’s largest ever individual research program, a major national initiative for strategically basic research, education and faculty recruitment. The program is initiated and generously funded by the Knut and Alice Wallenberg Foundation (KAW) with 2.6 billion SEK. In addition to this, the program receives support from collaborating industry and from participating universities to form a total budget of 3.5 billion SEK. Major goals are more than 50 new professors and more than 300 new PhDs within AI, Autonomous Systems and Software. The vision of WASP is excellent research and competence in artificial intelligence, autonomous systems and software for the benefit of Swedish industry. For more information about the research and other activities conducted within WASP please visit: http://wasp-sweden.org/

Requirements: 

A PhD position at the Division requires 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, as well as sufficient proficiency in oral and written English. Experience in machine learning or computational statistics is valued. The position is for a maximum of five years and includes departmental duties at a level of at most 20 % (typically teaching).

Application:

The application should include a statement (at most 2 pages) of the applicant’s motivation for applying for this position, including the candidate’s qualifications and research interests, which of the two problem formulated above you are most interested in and evidence of self-motivation and constructive teamwork. The application should also include a CV; degrees and grades (translated to English or Swedish); a copy of the Master’s thesis (or a draft thereof), publications, and other relevant documents. References with contact information and up to two letters of recommendation may be provided. Applications may be submitted by candidates that have not fully completed the Master of Science degree (or equivalent), however all applicants should state the earliest feasible starting date of employment.

Rules governing Ph.D. candidates are set out in the Higher Education Ordinance Chapter 5, §§ 1-7 and in Uppsala university's rules and guidelines http://regler.uu.se/search/?hits=30&languageId=1&search-language_en=English

Uppsala University strives to be an inclusive workplace that promotes equal opportunities and attracts qualified candidates who can contribute to the University’s excellence and diversity. We welcome applications from all sections of the community and from people of all backgrounds.

Salary: According to local agreement for PhD students and teaching assistants.
 
Starting date: As soon as possible, temporary position ending in maximum 5 years.

Type of position: Full time position.

For further information about the position please see http://www.it.uu.se/ (the department) or contact: Prof. Thomas Schön  (thomas.schon@it.uu.se) and Dr Dave Zachariah (dave.zachariah@it.uu.se).  

Please submit your application by 28th of October 2018, UFV-PA 2018/3295.

Are you considering moving to Sweden to work at Uppsala University? If so, you will find a lot of information about working and living in Sweden at www.uu.se/joinus. You are also welcome to contact International Faculty and Staff Services at ifss@uadm.uu.se.