2 Doctoral Student and 1 Post-Doctoral for Machine Learning, Sparse Signal Processing and Beyond 5G Wireless Systems University of Oulu, Infotech and Faculty of Information Technology and Electrical Engineering

Two doctoral student and one post-doctoral positions for machine learning, sparse signal processing and beyond 5G wireless systems (fully funded, 4 years positions).

TWO doctoral student and ONE post-doctoral positions for machine learning, sparse signal processing and beyond 5G wireless systems, 4-year position 2018-2022 in Infotech and Faculty of Faculty of Information Technology and Electrical Engineering, Centre for Wireless Communications, University of Oulu.

 

The University of Oulu (http://www.oulu.fi/english/) is one of the largest universities in Finland, with approximately 16 000 students and 3 000 employees. The University of Oulu Graduate School (UniOGS) (http://www.oulu.fi/uniogs/) provides the framework and conditions for high-quality, research-driven doctoral education at the University of Oulu, and field-specific doctoral training is provided by its multidisciplinary doctoral programmes. Infotech (http://www.oulu.fi/infotech/) offers a high-level international multidisciplinary environment supplied with cutting-edge infrastructures. Under this framework, the Information Technology and Electrical Engineering Doctoral Programme (ITEE-DP) (http://www.oulu.fi/uniogs/dp/iteedp) offers doctoral training in Electrical Engineering, Communications Engineering, Computer Science and Engineering and Information Processing Science.

 

Applications are invited for a full-time doctoral TWO student positions and ONE post-doc position for a maximum of four years, starting at the earliest on 1.06.2018 in an Infotech research project headed by Adj. Professor Marian Codreanu in the Centre for Wireless Communications research unit, Faculty of Information Technology and Electrical Engineering.

 

The emerging compressive sensing theory provides fundamentally new ways for acquisition, compression, transmission, processing, storage, and sharing of data. Our work aims to understand the fundamental design principles and investigate the ultimate capabilities of these sparse signal processing techniques in future Internet of Things applications (including, e.g., statistical inference for automatic process monitoring and distributed decision making) and beyond 5G wireless system optimization (including, e.g., initial link establishment, compressive channel estimation and transceiver optimization for mmWave communications as well as high resolution online signal reconstruction/estimation/denoising). We seek computationally efficient algorithms able to: 1) handle large amount of data in real time, and 2) perform inference, decision, signal estimation or classification tasks directly in the compressed domain (i.e., without first reconstructing the signal of interest).

 

The positions are supervised by Adj. Professor Marian Codreanu.

 

Requirements for a doctoral student

 

To successfully occupy the position of a doctoral student, the candidate must possess a Master’s degree or an equivalent degree (e.g. licentiate) preferably in electrical engineering, computer science or applied mathematics. Degree must have been completed with excellent grades by 30.5.2018 (or latest before the job contract starts). Ability to pursue independent research and excellent writing and fluency in English is expected. The doctoral student position is intended for an Early Stage Researcher (ESR) who, according to the ”European Charter for Researchers and the Code of Conduct for the Recruitment of Researchers”, is defined as a researcher in the first four years (full-time equivalent) of his/her research activity, including the period of research training. Applicants will be either starting their doctoral training, or will have completed no more than two full years of training (adjusted for possible previous part-time status) at the time the position is filled. The selected candidate will carry out his/her doctoral studies in the Information Technology and Electrical Engineering Doctoral Programme of the University of Oulu Graduate School (UniOGS) and must meet the minimal requirements to receive doctoral study rights as defined in http://www.oulu.fi/uniogs/requirements_for_admission.

 

Requirements for a post-doc

To successfully occupy the position of a post-doc researcher, the candidate must possess a doctoral degree preferably in electrical engineering, computer science or applied mathematics. Degree must have been completed by 30.4.2018 (or latest before the job contract starts). A successful applicant must have a solid mathematical background as well as an excellent publication track record (including, e.g., leading IEEE Journals and Transactions papers). Expertise in mathematical optimization, sparse signal processing, machine learning or statistical inference is a major advantage. Ability to pursue independent research and excellent writing and fluency in English is expected.

 

Salary

The salary of the selected doctoral student will be set on levels 2 – 4 of the national salary scale for the teaching and research staff of Finnish universities. In addition, a supplementary remuneration will be given for personal achievement and performance (max. 46.3%). The total salary for these levels (before tax) currently ranges from about 1985 to 3621 Euros/month for full-time employment.

 

The salary of the selected post-doc will be set on level 5 of the national salary scale for the teaching and research staff of Finnish universities. In addition, a supplementary remuneration will be given for personal achievement and performance (max. 46.3%). The total salary for these levels (before tax) currently ranges from about 2865 to 4191 Euros/month for full-time employment.

 

Application

Applications must be submitted using the electronic application form by 30.4.2018, 24:00 (Finnish local time), with the following attachments as three separate pdf files:

  • Complete CV containing contact information of at least two referees (Max. size limit of the attachment: 5 Mbytes)
  • Motivation letter (maximum 1 page) describing prior knowledge and research interests and career plans (1-2 pages; max. size limit of the attachment: 2 Mbytes).
  • Certificates/Diplomas: Scanned electronic copies of diplomas and transcripts of the records of relevant previous degrees. If the original documents are not in English, Finnish or Swedish, each document must be accompanied by an official certified translation into English or Finnish. (Max. size limit of the attachment: 2 Mbytes)

 

Other relevant information

The eligible applicants fitting best in the research profile expected for the position may be invited to an on-site or remote interview. All applicants will be notified when the selection process is completed.

 

Contact

- Dr. Marian Codreanu, e-mail: codreanu@oulu.fi

- Concerning the general requirements and application procedures: Coordinator Mirjami Jutila, e-mail: mirjami.jutila (at) oulu.fi

 


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