Two PhD student positions in Machine Learning

Updated: about 2 years ago
Deadline: 21 Mar 2022

Published: 2022-01-18

Uppsala University is a comprehensive research-intensive university with a strong international standing. Our ultimate goal is to conduct education and research of the highest quality and relevance to make a long-term difference in society. Our most important assets are all the individuals whose curiosity and dedication make Uppsala University one of Sweden’s most exciting workplaces. Uppsala University has over 54,000 students, more than 7,500 employees and a turnover of around SEK 8 billion.

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

Read more about our benefits and what it is like to work at Uppsala University

At the Division of Systems and Control we develop methodology and concrete tools for learning, reasoning and acting based on measured data. One of the cornerstones in our research is a probabilistic model allowing us to systematically represent and cope with the uncertainty that is inherent in most data. An important goal is to develop flexible models that can capture complex dynamical phenomena and their environments allowing machines and humans to better understand the world around us. The data and the model are two of the cornerstones of our research. The third cornerstone is the learning algorithm, with the fundamental objective of automatically constructing models based on data. It remains a major challenge to develop efficient and accurate learning algorithms capable of handling high-dimensional models, data rich applications, complex model structures, and diverse data sources that arise in many of the data analysis problems that we are currently facing. The fourth and final cornerstone of our research is that of control. The main task here is to make use of all that has been learnt from the data and represented within the probabilistic model to automatically make decisions and influence the current situation in a suitable manner. 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

The Division of Systems and Control has a wide network of strong international collaborators all around the world, for example at the University of Cambridge, University of Oxford, Imperial College, University of British Columbia, University of Sydney, University of Newcastle and Aalto University. We strive for all PhD students to get a solid international experience during their PhD.

Duties
The research projects for the advertised positions will be within the areas of machine learning. Two examples of potential research directions are briefly outlined below. As an applicant you are not required to specify a specific research topic in your application (but you are of course most welcome to do so if you want). Indeed, the topics below are provided mainly to make the advertised positions more concrete. We do welcome own initiatives and the precise research topic of each PhD student will be decided in a dialog between the student and the supervisor after a successful appointment. The problem formulations that are most relevant for this opening are the following:

  • Development of robust machine learning methods:
  • Machine learning (ML) methods leverage past training data to perform tasks that either assist or automate human decision-making. Most methods build on the assumption that data distributions from a training environment and future test environments will match each other. However, when these environments diverge, the task performance of state-of-the-art learning methods will degrade and may result in erroneous decisions. New methods that are robust to such divergences are needed in a wide range of applications, including wireless receiver localization, health diagnostics, and medical decision support. We seek to develop such methods through a cross-fertilization of ideas and tools from different branches of machine learning, statistics and optimization.

  • Developing flexible models for nonlinear dynamics:
  • Dynamical models are essential in explaining the world around us. When it comes to modeling nonlinear dynamics, flexible models have the potential to significantly enhance performance over simple ones. A key topic here is to design deep models with longer memories. Related to this is the task of deriving algorithms that can be used to learn the unknown model parameters from the measured data. If there is interest we will also look into applications within life science and medicine.

    The position is for a maximum of five years and includes departmental duties at a level of at most 20 % (typically teaching).

    Requirements
    A PhD position at the Division requires a completed (or near to completing) Master of Science, or equivalent in a field that is relevant to the topic of the PhD thesis, and good communication skills with sufficient proficiency in oral and written English. Personal characteristics, such as creativity, thoroughness and/or a structured approach, are essential. 

    Additional qualifications
    Experience and courses in machine learning or statistical theory is valued.

    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 and evidence of self-motivation and constructive teamwork. The application should also include a CV; degrees and grades (translated to English or Swedish); the 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. 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 PhD students are set out in the Higher Education Ordinance chapter 5, §§ 1-7 and in Uppsala University's rules and guidelines .

    About the employment
    The employment is a temporary position according to the Higher Education Ordinance chapter 5 § 7. Scope of employment 100 %. Starting date as soon as possible or as agreed. Placement: Uppsala.

    For further information about the position, seehttp://www.it.uu.se/ (the department) or contact: Prof. Thomas Schön  ([email protected]), Associate Prof. Dave Zachariah ([email protected]), or Prof. Peter Stoica ([email protected]).

    Please submit your application by 21 March 2022, UFV-PA 2022/137.

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    Submit your application through Uppsala University's recruitment system.


    Placement: Department of Information Technology

    Type of employment: Full time , Temporary position longer than 6 months

    Pay: Fixed salary

    Number of positions: 2

    Working hours: 100%

    Town: Uppsala

    County: Uppsala län

    Country: Sweden

    Union representative: ST/TCO [email protected]
    Seko Universitetsklubben [email protected]
    Saco-rådet [email protected]

    Number of reference: UFV-PA 2022/137

    Last application date: 2022-03-21


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