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Postdoctoral researcher in Machine learning – Computer science

Örebro University

Sweden

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Aug 20, 2021 23:59 (GMT +2)

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We are looking for a postdoctoral researcher in computer science for a fixed-term position at the School of Science and Technology.

General Info

Position: Postdoctoral researcher
No. of Positions: 1
Research Field: ,
Deadline to Apply: August 20, 2021 (GMT +2)
Joining Date: ASAP
Contract Period: 2 Years
Salary: According to Standard Norms

Workplace:
Division of Computer Science
School of Science and Technology
Örebro University
Örebro,

Qualification Details

Those qualified for appointment as a postdoctoral researcher are applicants who have been awarded a doctoral degree in a subject matter relevant for the position or have a degree from abroad deemed to correspond to a doctoral degree. The degree is to have been awarded no more than three years prior to the application deadline. If special grounds exist, a person who has been awarded their doctoral degree prior to that should also be considered. Such grounds comprise leave of absence due to illness, parental leave, clinical practice, positions of trust in a trade union or other similar circumstances.

Assessment criteria

The basis for assessment is the applicant’s scientific expertise, skill, and knowledge in the subject matter. Particular attention is paid to the applicant’s prospects to contribute to research and the demonstrated ambition to embark on a career within academia as well as the ability and suitability to collaborate with other members of the research environment.

Other assessment criteria
The applicant should possess and demonstrate:

  • A strong background in computer science, machine learning, or robotics
  • Motivation to obtain to undertake research on an international level
  • Strong mathematical background
  • Prior research experience in the areas of machine learning or robotics
  • A track record of high-quality publications in the areas of machine learning or robotics
  • Excellent programming skills
  • Excellent communication skills in English

Responsibilities/Job Description

The appointment as a postdoctoral researcher is intended to enable persons who have recently been awarded their doctoral degree, to consolidate and develop primarily their research skills.

This position is primarily focused on research. Further, it is expected that the postdoctoral researcher assists in supervision of doctoral students, takes an active role in developing the research environment, and contributes to the research environment, e.g., by collaborating with other researchers.

How to Apply?

Online Application through "Apply Now" Button from this page or from advertisement webpage (URL below)

Reference Number: ORU 2.1.1- 02840/2021
(If any, use it in the necessary place)

Documents Required

For the application to be complete, the following electronic documents must be included:

  • Covering letter, outlining why you are interested in this position and how you believe you can contribute to the continued development of our research environment at Örebro University. The cover letter should indicate one of the two directions listed above as a primary area of interest.
  • CV with a relevant description of your overall qualifications and experience relevant to this position.
  • Account of research qualifications and experience relevant to this position.
  • Copies of relevant course/degree certificates and references verifying eligibility and criteria met.
  • Most relevant scientific publications (maximum of 3 and in full-text format)

Only documents written in English, Swedish, Norwegian and Danish can be reviewed.

About the Project

The topic for this position is continual learning and learning with dataset shift. There are two direction for this position and we are looking to recruited a postdoctoral research for both or either of the two directions.

Direction 1 entails fundamental research on continual learning for dataset shift with data efficient and interpretable models and algorithms. This direction investigates methods for learning, updating, and forgetting for domains where data is incrementally available or changes over time (e.g. models of system dynamics, robotic mapping, reinforcement learning, or environmental data). Prior knowledge, experience, and interest in probabilistic machine learning, statistical learning, and Gaussian Processes are expected for this direction. In addition, prior knowledge, experience, and interest in Bayesian methods and deep Gaussian processes are advantageous.

Direction 2 entails fundamental research on reinforcement learning with continual adaptation and dataset shift including, but not limited to, meta and transfer learning methods. This direction investigates methods for fast and efficient reinforcement learning in real-world settings by exploiting knowledge transfer, e.g. from other domains or experience, to allow faster learning and adaptation in the target environment. Prior knowledge, experience, and interest in reinforcement learning in continuous spaces and deep learning are expected for this position. Prior knowledge, experience, and interest in robotic perception and control as well as probabilistic machine learning are advantageous.

The position is funded through the Wallenberg AI, Autonomous Systems, and Software Program (WASP, https://wasp-sweden.org/) and is not tied to a particular research project. It therefore provides a large degree of freedom to the appointed postdoctoral researcher. Research in this project will be performed in close collaboration with doctoral students and postdoctoral researchers in the same research environment, as well as external collaborators.

About the Employer: Örebro University

Note or Other details

As directed by the National Archives of Sweden (Riksarkivet), we are required to deposit one file copy of the application documents, excluding publications, for a period of two years after the appointment decision has gained legal force

Contact details

For more information about the position, contact Johannes A. Stork (Supervisor), +46 19 30 39 40, e-mail: johannes.stork@oru.se, or Lars Karlsson (Head of Unit), +46 19 30 33 55, e-mail: lars.karlsson@oru.se, Peter Johansson (Head of School), +46 19 30 32 75, e-mail: peter.johansson@oru.se for administrative questions.

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