Postdoc in Large-scale distributed machine learning - Hiring in process/Finished, not possible to apply

Job description

With the development of computing and communication technologies, and emerging data-driven applications, e.g., IoT based intelligent systems, social network analysis and vehicular networks, the volume of data for various learning systems increases explosively along with the number of involving computing nodes. Thus, large-scale distributed machine learning (e.g., federated learning, and alternating direction method of multipliers (ADMM)) has been pervasive in our societies and industries. However, the practical performance of DML is often limited by various bottlenecks and is still far from theoretical upper limits. Thus, this project will develop efficient theories, algorithms and schemes to achieve reliable, secure and low-complexity large-scale DML. One key approach is to exploit network and channel coding schemes. Theoretical analysis will be performed using learning and communication tools (e.g., graph model, coding and information theory, optimization). The result will also be verified by simulations with true data.

The project will be hosted by the Division of Information Science and Engineering, EECS school. The project is funded by Swedish Research Council (VR). You will have opportunities to work on cutting-edge information and data science and engineering.

What we offer

• A position at a leading technical university that generates knowledge and skills for a sustainable future
• Engaged and ambitious colleagues along with a creative, international and dynamic working environment
• Work in Stockholm, in close proximity to nature
• Help to relocate and be settled in Sweden and at KTH

Read more about what it is like to work at KTH

Qualifications

Requirements

• A doctoral degree or an equivalent foreign degree. This eligibility requirement must be met no later than the time the employment decision is made.
• Strong track records (publications) in machine learning/data science.
• Knowledge in related mathematical analysis (for machine learning).
• Knowledge in information theory, coding theory is preferable.

Preferred qualifications

• A doctoral degree or an equivalent foreign degree, obtained within the last three years prior to the application deadline.
• Showed capability of collaborating with others.
• Being able to analyse and work with complex issues, especially with mathematical tools.
• Demonstrated the capability of independently writing research articles in English.
• Teaching abilities.
• Awareness of diversity and equal opportunity issues, with specific focus on gender equality.

Great emphasis will be placed on personal skills.

Trade union representatives

You will find contact information to trade union representatives at KTH's webbpage.

To apply for the position

Log into KTH's recruitment system in order to apply for this position. You are the main responsible to ensure that your application is complete according to the ad.

The application must include:

• CV including relevant professional experience and knowledge.
• Copy of diplomas and grades from your previous university studies. Translations into English or Swedish if the original documents have not been issued in any of these languages.
• Brief account of why you want to conduct research, your academic interests and how they relate to your previous studies and future goals. Max two pages long.
• Five most important publications.
• The contact information of three references.

Your complete application must be received at KTH no later than the last day of application, midnight CET/CEST (Central European Time/Central European Summer Time).

About the employment

The position offered is for, at the most, two years.

A position as a postdoctoral fellow is a time-limited qualified appointment focusing mainly on research, intended as a first career step after a dissertation.

Others

Striving towards gender equality, diversity and equal conditions is both a question of quality for KTH and a given part of our values.

For information about processing of personal data in the recruitment process please read here.

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Disclaimer: In case of discrepancy between the Swedish original and the English translation of the job announcement, the Swedish version takes precedence.