University of Copenhagen, Department of Computer Science

3462 13990
Position ID:UCPH-Department of Computer Science-PHDTHEMACH [#13990]
Position Title: PhD fellow in Theoretical Machine Learning
Position Type:Student programs
Position Location:Copenhagen, Hovedstaden 2100, Denmark [map]
Subject Areas: Machine Learning / Machine Learning
Computer Science / Artificial intelligence and machine learning
Appl Deadline:2019/09/01 (posted 2019/07/02, listed until 2019/09/01)
Position Description:    

*** the list date or deadline for this position has passed. ***

Department of Computer Science
Faculty of Science

University of Copenhagen

 

The position is open from 1 October 2019 or as soon as possible thereafter.

Description of the scientific environment
The student will work in the Machine Learning Theory group of Associate Professor Yevgeny Seldin https://sites.google.com/site/yevgenyseldin/ The group is part of the Machine Learning section https://di.ku.dk/english/research/machine-learning/ and SCIENCE AI Center https://ai.ku.dk/

Project description

The project, titled “Theoretical Foundations of Learning with Worst-Case and Easy Data”, will focus on development and analysis of online learning algorithms that can successfully operate over ranges of online learning environments. Examples of such algorithms include algorithms for stochastic and adversarial bandits https://arxiv.org/pdf/1807.07623 and algorithms for adaptation to easy data in prediction with limited advice https://arxiv.org/pdf/1807.00636.

Read more about the Department at http://www.science.ku.dk/english/about-the-faculty/organisation/.

 Please find the full job advertisement at http://employment.ku.dk/.

Only electronic applications are accepted.

 Application due: 9/1/2019

Apply



Part of the International Alliance of Research Universities (IARU), and among Europe’s top-ranking universities, the University of Copenhagen promotes research and teaching of the highest international standard. Rich in tradition and modern in outlook, the University gives students and staff the opportunity to cultivate their talent in an ambitious and informal environment. An effective organisation – with good working conditions and a collaborative work culture – creates the ideal framework for a successful academic career.

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Contact: Yevgeny Seldin
Postal Mail:
University of Copenhagen
Department of Computer Science
Universitetsparken 1
2100 Copenhagen
Denmark
Web Page: https://ai.ku.dk/

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