job description
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PhD position in Generalized Driven Distributed Continuous Machine Learning
Electrification and digitization is one of the biggest areas of the future shift towards a sustainable society. The Department of Electrical Engineering has been successful in the fields of renewable energy, electric vehicles, industrial IoT, artificial intelligence, 6G communications and wireless sensor networks, as well as in research and education in life sciences, smart electronic sensors and medical systems. The Department of Electrical Engineering is an international workplace with approximately 160 employees, all of whom contribute to important technological challenges in energy and health at the Ångström Laboratory.
The position will be based in the Signals and Systems department of the Faculty of Electrical Engineering. There is a friendly working environment and a strong research program. The Signals and Systems Department cooperates with public and private companies in Sweden and with stakeholders in different research areas. We look forward to receiving your application. Join us and build the future with us!
About the projectMachine learning methods can usually only solve specially trained tasks. They first adapt (train) a mathematical model on a large number of examples and then apply the trained model. However, when the trained model encounters new situations, its performance drops dramatically. In other words, these systems may not generalize well: they perform poorly in scenarios that are relevant but different from the trained ones. This poses a major obstacle to the effective and reliable use of machine learning in real-world applications.
We need to find training methods and model structures that can learn to master new situations without unduly forgetting previously learned knowledge. This project will investigate and develop such models that allow for continuous learning. We will focus on continuous learning in situations where multiple devices cooperate and learn together, i.e. distributed learning. Such situations are of great practical interest, but can make generalization more difficult to achieve. We will use structural insights from mathematical analyses of these problems to develop and evaluate continuous learning methods that enable generalization.
hold a Master’s (Phase II) degree in Engineering Physics, Electrical Engineering, Machine Learning, Data Science, Computer Science, Applied Mathematics, or a similar field, or
have completed a minimum of 240 credits of post-secondary education in one of these fields, with a minimum of 60 credits, including an independent project worth at least 15 credits, or
otherwise acquired substantially equivalent knowledge.
Other qualificationsWe are looking for candidates with:
Strong interest in developing new machine learning theories and methods
Strong mathematical background
Proficiency in programming (preferably Python)
Good oral and written English
Organized, self-motivated, and independent approach to technical work and good collaboration skills
Emphasis on courses or other experience in the following disciplines: optimization, linear algebra, signal processing, probability, stochastic processes, statistical machine learning, and deep learning.
Regulations concerning PhD students are contained in Chapter 5, Sections 1-7 of the Higher Education Regulations and in the regulations and guidelines of Uppsala University.
Learn more about our benefits and what it is like to work at Uppsala University https://uu.se/om-uu/jobba-hos-oss/.
offer requirements
To meet the entry requirements for the PhD, you must
hold a master’s (second stage) degree in engineering physics, electrical engineering, machine learning, data science, computer science, applied mathematics, or a similar field, or
have completed a minimum of 240 credits of higher education in these fields, with a minimum of 60 credits at the master’s level, including an independent project worth independent project of at least 15 credits, or
has otherwise acquired substantially equivalent knowledge.
Other qualificationsWe are looking for candidates with:
Strong interest in developing new machine learning theories and methods
Strong mathematical background
Proficiency in programming (preferably Python)
Good oral and written English
Organized, self-motivated, independent approach to technical work and good collaboration skills
Emphasis on courses or other experience in the following disciplines: optimization, linear algebra, signal processing, probability, stochastic processes, statistical machine learning, and deep learning.
Regulations concerning PhD students are contained in Chapter 5, Sections 1-7 of the Higher Education Regulations and in the regulations and guidelines of Uppsala University.
Learn more about our benefits and what it is like to work at Uppsala University https://uu.se/om-uu/jobba-hos-oss/.
offer benefits/salary
Uppsala University is a wide-ranging research university of international importance. The ultimate goal of Uppsala University is to carry out education and research of the highest quality and relevance, contributing to society. Our most important assets are our 7,600 employees and 53,000 students who, with curiosity and dedication, make Uppsala University one of the most exciting places to work in Sweden.
Learn more about our benefits and what it is like to work at Uppsala University https://uu.se/om-uu/jobba-hos-oss/.