Two PhD Positions: Computer Science, Machine Learning
The Department of Computing Science, Umeå University Sweden is looking for outstanding candidates for a doctoral position (PhD position) in Computer Science with focus on distributed deep learning anomaly detection for distributed clouds and Internet of Things (IoT). This PhD position is funded by The Knut and Alice Wallenberg Foundation through The Wallenberg AI, Autonomous Systems and Software Program (WASP), Sweden.
Overview
Two PhD position is aimed for studies in Computing Science within the distributed systems research group, but collaboration with researchers in, e.g., mathematical statistics, machine learning, optimization, deep learning or artificial intelligence is expected. (For further information, see www.cloudresearch.org).
The main objectives are to develop methods, primarily distributed deep learning algorithms, for anomaly detection, prediction and diagnosis in distributed clouds and IoT by taking advantages of multilayer cloud architecture from edge to datacenter.
Required Qualifications
- The candidate is required to have completed a second-cycle level degree, or completed course requirements of at least 240 ECTS credits, of which at least 60 ECTS credits are at second-cycle level, or have an equivalent education from abroad, or equivalent qualifications.
- Documented knowledge and a solid background in machine learning and/or distributed systems is a requirement. The research is to a large extent interdisciplinary, and a broad competence profile and experience from other relevant areas (such as machine learning, distributed learning, IoT, discrete optimization, and statistical methods) is considered a merit.
- To fulfill the specific entry requirements for doctoral (PhD) studies in computing science the applicant is required to have completed courses at second-cycle level degree equivalent to 60 ECTS credits in computing science, or in another subject considered to be directly relevant for the specialization in question.
- Good skills in both spoken and written English are a requirement for the position.
- Important personal qualities are, beside creativity and a curious mind, the ability to work both independently and in a group and experience in the scientific interaction with researchers from other disciplines and in other countries.
Terms of employment
The position is aimed for PhD studies and research during four years, leading to a PhD degree. It is mainly devoted to postgraduate studies (at least 80% of the time), including to take part in the WASP Graduate School, but may include up to 20% department service (usually teaching). If so, the total time for the position is extended accordingly (up to maximum five years). The employment will start as soon as possible, or as otherwise agreed.
How to apply:
The application must be written in English or Swedish, Documents must be in Word or pdf format. Application must be submitted electronically using the e-recruitment system of Umeå University, and be received no later than January 15, 2020.
Send a complete application having the following documents:
- A curriculum vitae
- A cover letter including a description of your research interests, your reasons to apply for the position, and your contact information
- Reprints / copies of Bachelors / Master’s thesis, and other relevant publications, if any
- Copies of degree certificates and other completed academic courses
- Documentation and description of other relevant experiences or competences, such as from software development and work in or with industry.
- Contact information for three reference persons
Further information:
Write to Assistant Professor Monowar Bhuyan, (email: monowar@cs.umu.se) and Professor Erik Elmroth (email: elmroth@cs.umu.se).
Organization | Department of Computing Science, Umeå University, Sweden |
Type of position | Doctoral |
Subject | Computing Science |
Contact | Monowar Bhuyan, biträdande ector,
Email: monowar@cs.umu.se |
Closing date | January 15, 2020, 11:59 PM CET |
Reference | AN 2.2.1-1886-19 |
More information:
Position 1: PhD position with a focus on distributed deep learning
Position 2 – PhD position with a focus on trustworthy learning