ORGANISATION/COMPANYUniversity of Stavanger
RESEARCH FIELDComputer science › Other
RESEARCHER PROFILEFirst Stage Researcher (R1)
APPLICATION DEADLINE08/03/2020 23:00 - Europe/Brussels
LOCATIONNorway › STAVANGER
TYPE OF CONTRACTTemporary
HOURS PER WEEK37,5
The University of Stavanger invites applicants for a Ph.D fellowship in Deep Learning at the Faculty of Science and Technology, Department of Electrical Engineering and Computer Science. The postition is vacant from June 1st 2020, or after appointment.
This is a trainee position that will give promising researchers an opportunity for academic development leading to a doctoral degree.
The appointment is for three years with research duties exclusively, or four years with both research and 25% compulsory duties. This will be clarified in the recruitment process.
Project Title: Smart Distributed Algorithmic Solutions to Scale Deep Learning
Deep Neural Networks (DNNs) have become central to several machine learning applications such as computer vision, natural language processing, question answering etc. As the size of data collections used to train these models continue to grow, the number of parameters used in the DNNs have grown as well. For example, recent models such as BERT and XLNet have hundreds of millions of parameters and take several days to train on state-of-the-art hardware. Relying on hardware alone to scale is no longer an option as the Moore’s law doesn’t seem to support performance increases in GPUs and TPUs. Another issue with use of such large models is the efficiency at inference time. The goal of this project is to develop smart algorithmic solutions that take advantage of distributed and parallel architectures to scale both DNN training and inference for massive datasets. For example, recent works have used Locality Sensitive Hashing (LSH) to minimize matrix multiplications required to train the DNNs, use of approximate gradient updates and pruning search space at inference time etc. While these preliminary works show promising results they are not applicable for a variety of DNNs such as convolutional neural networks, recurrent neural networks, attention networks and graph neural networks. Moreover, use of such algorithms to exploit distributed architectures is also an open challenge.
We are looking for applicants with a strong academic background who have completed a five-year master degree (3+2) within Computer Science, Data Science, preferably acquired recently; or possess corresponding qualifications that could provide a basis for successfully completing a doctorate.
Candidates with experience or publications related to machine learning, deep learning and distributed systems will be prioritized.
To be eligible for admission to the doctoral programmes at the University of Stavanger both the grade for your master’s thesis and the weighted average grade of your master’s degree must individually be equivalent to or better than a B grade.
If you finish your education (masters degree) in the spring of 2020 you are also welcome to apply.
Applicants with an education from an institution with a different grade scale than A-F should attach a confirmed conversion scale that shows how the grades can be compared with the Norwegian A-F scale.
Emphasis is also placed on your:
- ability to demonstrate interest in scientific research. The evaluation considers many aspects of excellence, as well as the personal drive and organizational skills
- motivation and potential for research within the field
- ability to work independently and in a team, be innovative and creative
- ability to work structured and handle a heavy workload
- having a good command of both oral and written English
- a strong research environment with supervision from experienced faculty opportunities to collaborate and for research stays with our renowned collaborators worldwide, including Max-Planck Institute for Informatics, L3S research centre in Germany, Aalborg University, Denmark and University of Amsterdam, Netherlands
- varied duties in a large, exciting and socially important organisation
- an ambitious work community which is developing rapidly. We strive to include employees at all levels in strategic decisions and promote an informal atmosphere with a flat organisational structure
- colleague-based guidance programme (NyTi) if teaching is a part of your Ph.D
- salary in accordance with the State Salary Scale, l.pl 17.515, code 1017, NOK 479.600,- gross per year with salary development according to seniority in the position
- automatic membership in the Norwegian Public Service Pension Fund, which provides favourable insurance- and retirement benefits
- favourable membership terms at a gym and at the SIS sports club at campus
- employment with an Inclusive Workplace organisation which is committed to reducing sick leave, increasing the proportion of employees with reduced working capacity, and increasing the number of professionally active seniors
- "Hjem-jobb-hjem" discounted public transport to and from work
- as an employee in Norway, you will have access to an optimal health service, as well as good pensions, generous maternity/paternity leave, and a competitive salary. Nursery places are guaranteed and reasonably priced
- relocation programme in event of moving to Norway, including support and language courses for spouses
The appointee will be based at the University of Stavanger, with the exception of a stay abroad at a relevant centre of research.
It is a prerequisite that the appointee has a residence which enables him or her to be present at/available to the academic community during ordinary working hours.
The University currently employs few female research fellows within this academic field, and women are therefore particularly encouraged to apply.
The position has been announced in both Norwegian and English. In the case of differences of meaning between the texts, the Norwegian text takes precedence.
More information on the position can be obtained from Associate Professor Vinay J. Setty, tel: +47 5183 2760, e-mail: firstname.lastname@example.org or Head of Department Tom Ryen, tel: +47 5183 2029, e-mail: email@example.com
Information about the appointment procedure can be obtained from HR-adviser Janne Halseth, tel: +47 51833525, e-mail: firstname.lastname@example.org
To apply for this position please follow the link "Apply for this job". Register your application and CV including relevant education and work experience. In your application letter you must show your research interests and motivation to apply for the position.
The following documents must be uploaded as attachments to your application in separate files:
- list of publications
- other documentation that you consider relevant
The documentation must be available in either a Scandinavian language or in English. If the total size of the attachments exceeds 30 MB, they must be compressed before upload. Information and documentation to be taken into account in the assessment must be submitted within the application dealine.
Please note that information on applicants may be published even if the applicant has requested not to be included in the official list of applicants - see Section 25 of the Freedom of Information Act.
UiS only considers applications and attachments registered in JobbNorge.
UiS - challenge the well-known and explore the unknown
The University of Stavanger (UiS) has about 12,000 students and 1,800 employees. We are the only Norwegian member of the European Consortium of Innovative Universities. The university has high ambitions. We will have an innovative and international profile, and will be a driving force in knowledge development and in the process of societal change. Together with our staff and students, we will challenge the well-known and explore the unknown.
Department of Electrical Engineering and Computer Science is part of the Faculty of Science and Technology. The department carries out research within computer science, data Science, cybernetics and signal processing, and offers bachelor programs in electrica engineering and computer science, master programs in computer science, data science and cybernetics/signal processing, and a PhD program in information technology. There are currently 50 employees, including research fellows and postdocs, and 600 students at the department.
EURAXESS offer ID: 492573
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