Postdoc Computing Science (Robust Machine Learning)
The position is at the Department of Computing Science at Umeå University, Sweden. The selected candidate is expected to contribute towards the local research community by actively participating in the departmental and group research activities such as workshops, seminars, etc.
This project aims to design and implement robust learning and data-centric optimization techniques for advancing state-of-the-art machine learning algorithms where data is geographically distributed, sensitive, and scarce.
- Robust machine learning and data-centric optimization algorithms empower models through multi-level (local, global and hybrid) training, learning, and inference with data-centric optimization for scarce data and non-standard model settings.
- By creating unique features (e.g., decentralized training, learning and inference, fault-tolerant against failures and attacks, data-centric optimization, robustness), this project addresses the challenges in the following areas: robust learning; learning with scarce data and non-standard model settings; lack of theoretical knowledge to build manual models; computation efficient learning and optimization for obtaining more accurate and robust models with applications to constraint environments (i.e., Industrial Internet of Things (IIoT), healthcare systems) and edge infrastructures.
- These contributions can be within autonomous distributed systems lab, but collaboration with researchers in, e.g., machine learning, mathematical statistics, optimization, trustworthy learning and artificial intelligence is expected. (For further information, see www.cloudresearch.org).
- Applicants must have earned a PhD or a foreign degree that is deemed equivalent to a PhD in Artificial Intelligence, Machine Learning or Optimization for Machine Learning, Computer Science or a subject relevant for the position.
- The PhD degree should not be more than three years old by the application deadline, unless special circumstances exist. PhD in Computer Science, Computer Science and Engineering, Information Technology, Machine Learning, Machine Learning Perspective Optimization
- Candidates are expected to have outstanding knowledge of machine learning and optimization techniques. Demonstrable knowledge of data wrangling and learning in decentralized settings is a prerequisite.
- Experience in any of the areas robust learning, fault-tolerant learning and data-centric optimization when data is geographically distributed, sensitive and scarce is a merit.
- Since research is conducted in an international research environment, the ability to collaborate and contribute to teamwork, and an excellent command of the English language, both written and spoken, are essential requirements.
- We particularly invite female candidates to apply to ensure gender balance.
A complete application should contain the following documents:
- 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.
- Curriculum Vitae (CV) including a complete list of scientific publications.
- A copy of your PhD thesis and copies of (max 5) original research publications relevant to the above topics, numbered according to the publication list.
- Copies of degree certificates, including documentation of completed academic courses and obtained grades
- Names and contact information for three persons willing to act as references.
- Any other information relevant for the position such as description of software development experience, or previous industry experience.
- The application must be written in English or Swedish. Documents must be in Word or pdf format. Applications must be submitted electronically using the e-recruitment system of Umeå University, and be received no later than August 10, 2020.
- Further information can be obtained from Assistant Professor Monowar Bhuyan, (email: email@example.com) and Professor Erik Elmroth (email: firstname.lastname@example.org).
Register and apply here:
Assistant Professor Monowar Bhuyan, Department of Computing Science
Umeå University, Sweden
|Organization||Umeå University, Sweden|
|Fellowship Level||Postdoc with regular salary for two years|
|Subject areas||Machine Learning/Data-centric optimization|
|Fellowship amount||Will fix based on experience!|
|Deadline||August 10, 2020|