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Master Thesis: Mitigating Misclassification under Distribution Shift using at Ericsson

Stockholm, , Sweden -

Full Time

Start Date

Immediate

Expiry Date

07 Jan, 26

Salary

0.0

Posted On

09 Oct, 25

Experience

0 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Artificial Intelligence, Machine Learning, Data Science, Computer Science, Programming, Python, Probability Theory, Statistics

Industry

Telecommunications

Description

- Currently pursuing a master's degree in an AI/ML-related data science program, or in a related field such as computer engineering, electrical engineering, physics engineering, or similar. - Basic proficiency in computer science and in programming with Python. - Good knowledge of machine learning, probability theory, and statistics. The chance to use your skills and imagination to push the boundaries of what´s possible. To build solutions never seen before to some of the world's toughest problems. You´ll be challenged, but you won't be alone. You´ll be joining a team of diverse innovators, all driven to go beyond the status quo to craft what comes next. What happens once you apply? Click Here to find all you need to know about what our typical hiring process looks like. We truly believe that by collaborating with people with different experiences we drive innovation, which is essential for our future growth. learn more. Primary country and city: Sweden (SE) || Stockholm Req ID: 774151

Responsibilities

The role involves conducting research to mitigate misclassification under distribution shift using conformal prediction. You will collaborate with a diverse team to develop innovative solutions to complex problems.