Mater thesis: Characterizing video compression using deep learning algorithmsJob Summary i Luleå

We are looking for a MSc Thesis student who is interested in image analysis, neural networks and video compression. The main objectives for the work are:

• Research state of the art image classification networks
• Collect data to investigate and train a model on.
• Train a network to be able to describe the compression degradations that video encoding has added to the film.
• Try to predict how dissatisfied a customer or user would be if using a video service where a certain level of video quality was experienced.

Key Qualifications:

• You have studied computer science and data communication
• Knowledge of media compression
• Experience with deep learning algorithms or other machine learning techniques
• You have completed the courses for your degree and are ready to start your MSc thesis
• Good programming skills in Python/Scikit-learn
• Strong analytical skills and ability to acquire new knowledge and apply it in the job 
• Good communication skills in written and spoken English
• Ability to formulate problems and solve them independently 
• Creativity and ability to work independently
• Presenting & Communicating

Applications should include a short motivation letter, CV, and transcripts of records. Candidates are invited to send their applications as soon as possible.

Location: Luleå

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Ericsson complies with applicable country, state and all local laws governing nondiscrimination in employment in every location across the world in which the company has facilities. In addition, Ericsson supports the UN Guiding Principles for Business and Human Rights and the United Nations Global Compact.

This policy applies to all terms and conditions of employment, including recruiting, hiring, placement, promotion, termination, layoff, recall, transfer, leaves of absence, compensation, training and development.

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Primary country and city: Sweden (SE) || || Luleå || 21094

Req ID: 216143