Postdoctoral Researcher in Distributed Machine Learning

5 months ago


Gothenburg, Sweden Chalmers tekniska högskola Full time

Project description
The (DSAI) is recruiting a postdoctoral researcher within the area of distributed machine learning (ML). The goal of this position is to advance the existing understanding and techniques for performing distributed ML tasks in the current and emerging scenarios. Distributed ML is a rapidly growing field (such as in federated learning), and the research in this area will have a great impact on a wide range of real-world applications. Our interest includes, but is not limited to, developing modern ML methods addressing privacy, data heterogeneity, domain shift, decentralization and communication/computation limitations. As a continuation of an ongoing research about the statistical theory of learning and distributed optimization, this work is intended to extend our recently developed methodologies to the aforementioned research topics.

Information about the division and the department
The division of DSAI at the is involved in various research activities around topics of data science and artificial intelligence. We strive to advance techniques for machine learning with guaranteed performance through theoretical analysis, and highly welcome collaborative efforts in this area. The candidate will join an ongoing research program about distributed ML, which aims to provide a deeper theoretical insight into this subject, and develop more advanced applied techniques. The DSAI division has a vibrant research environment and the candidate has a possibility of collaboration with PhD students and other researchers. The position is intended for the duration of fall 2024 - fall 2026.

Major responsibilities
The candidate is expected to conduct a research in the above areas, which involve extending our previous results on the performance of distributed ML methods to understand privacy preservation and handling data heterogeneity, among other potential topics. However, the topic of research and the domain of application can be flexible and the candidate is encouraged to suggest and pursue new directions, or develop new collaborative efforts (academic or industrial). The candidate is also expected to assist with supervision of PhD students and be involved, in part, in relevant teaching activities.

Qualifications
We invite candidates with a wide range of relevant background to apply for this position. A PhD degree within a suitable field of research is required, which may include computer science, mathematics, electrical engineering or similar areas. Experience in machine learning, distributed systems or distributed optimization, and familiarity with theoretical analysis methods in machine learning, especially statistical approaches, are highly appreciated. Please do not hesitate to contact us if you are unsure about your qualifications.

Mandatory
Phd degree in computer science, mathematics, electrical engineering or similar areas.

Meritous
Educational background in mathematical optimization, statistics and theory of machine learning

Contract terms
This postdoc position is a full-time temporary employment for two years.
We offer Chalmers offers a cultivating and inspiring working environment in the coastal city of . 



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