Postdoc position in Computer Science, machine learning 1960 views

The Department of Computing Science Umeå University Sweden is looking for candidates for a postdoctoral position in resource-frugal federated learning for preserving security and privacy with focus on edge infrastructures. The position is sponsored by The Knut and Alice Wallenberg Foundation through The Wallenberg AI, Autonomous Systems and Software Program (WASP), Sweden. http://wasp-sweden.org/.

This project focuses on design and implementation of resource-frugal and robust federated learning algorithms for preserving security and privacy, which are ideally suited for big-data and edge infrastructures. This project leverages federated learning techniques for advancing state-of-the-art machine learning algorithms where data is geographically distributed and sensitive. Federated learning algorithms empower large-scale distributed nodes, i.e., mobile devices to train globally shared models without divulging the privacy of raw data.

These contributions can be within distributed systems research group, but collaboration with researchers in, e.g., machine learning, optimization, deep learning, mathematical statistics, trustworthy learning or artificial intelligence is expected. (see www.cloudresearch.org).

Expected starting date is August 1, 2020 or as otherwise agreed. The appointment is for two years full-time employment. Postdocs are typically offered the opportunity to gain teaching experience on suitable undergraduate courses.

Required Qualifications

Applicant must have earned a Ph.D. degree or a foreign degree that is deemed equivalent to a Ph.D. in Artificial Intelligence, Computer Science, Machine Learning or a subject relevant for the position. The Ph.D. degree should not be more than three years old by the application deadline unless special circumstances exist.

Applicants are expected to have outstanding knowledge of machine learning techniques (preferably federated learning and trustworthy learning). Demonstrable knowledge of data privacy, deep learning, data wrangling, threats to machine learning, security and performance anomalies is a prerequisite. In particular, candidates should be well acquainted with modeling and implementing decentralized learning models to ensure security and privacy when data is geographically distributed and sensitive.

Since research is conducted in an international research environment, the ability to work as well independently as to collaborate and contribute to teamwork is required. Very good commands of the English language, both written and spoken, are key requirements.

We particularly invite female candidates to apply to ensure gender balance.

How to Apply

The application must be written in English or Swedish. Documents must be in Word or pdf format. Candidates must be submitted electronically using the e-recruitment system of Umeå University, and be received no later than April 20, 2020. Reference number AN 2.2.1-409-20 .

1. Curriculum Vitae (CV) including a complete list of scientific publications.
2. An introductory letter including a 2-page statement of research interests relative to the above topics and a motivation of why your expertise is appropriate for the position.
3. A copy of your Ph.D. thesis and copies of (max 5) original research publications relevant to the above topics, numbered according to the publication list.
4. Copies of degree certificates, including documentation of completed academic courses and obtained grades
5. Any other information is relevant for the position such as the description of software development experience, or previous industry experience.
6. Names and contact information for three persons willing to act as references.

Further information

Information can be obtained from Assistant Professor Monowar Bhuyan, (email: monowar@cs.umu.se) and Professor Erik Elmroth (email: elmroth@cs.umu.se). 

Further information