Ph.D. fellowship position in Bio-Inspired Artificial Intelligence

OsloMet – Oslo Metropolitan University is Norway’s third largest university, with nearly 22,000 students and 2,200 employees. Through the students we educate and the research we produce, the university has a direct impact on society, both in Norway and beyond. The university has two campuses, one in central Oslo and another a short distance from the city in the municipality of Lillestrøm. OsloMet is home to some of Norway’s largest and oldest educational programmes, including degree programmes in nursing, engineering and teacher education. The university is also a hub of research and technological innovation aimed at strengthening and sustaining the Norwegian welfare state.

The Faculty of Technology, Art and Design (TKD) offers higher education and research and development (R&D) activities within technical subjects, arts and design. The Faculty has approximately 4.000 students and 400 staff members and is situated at Pilestredet Campus in downtown Oslo and at Kjeller Campus in Viken.

The Department of Computer Science offers three bachelor’s degree programmes, a master’s degree programme, and is part of a cross-departmental PhD program. Academic staff at the department are pursuing research in a wide range of areas including computer science, the natural sciences, and innovation and management. Both students and researchers are also involved in an increasing number of interdisciplinary initiatives across the university.

At the Department, we are offering a PhD fellowship position. The successful applicant will be affiliated with the OsloMet Artificial Intelligence Lab and collaborate in the area of “Biologically inspired computational systems” with the Center of Research Excellence, NordSTAR.

This position will focus on some of the main tasks of the EvoDevo2Learn project. Natural selection operates at the level of genetic and epigenetic factors to select the set of genes. These genes, when expressed in the right sequence over the lifetime (development), will give rise to the growing structure (the brain, body) that has the potential to behave and learn with or without supervision. Moreover, and perhaps more strikingly, living organisms reliably learn during brain development; that is, when the structure of the network is changing drastically. Visual-spatial understanding of the world, spatiotemporal causality inference and sense of agency that underpins common sense, motor control, and even language are examples of competencies acquired during brain growth. Yet, how associative learning can emerge from the combination of evolutive and developmental mechanisms remains elusive. This project will use a novel approach to design and train biologically plausible networks of artificial neurons that combine evolution, development, and experience of embodied agents to overcome one or more of these grand challenges in AI. These agents will be trained in progressively more complex environments, which will be modeled after classical psychological, neuroscience and reinforcement learning experiments. The resulting population of functional algorithms will be further analyzed in two aspects:

The candidate’s project will intersect some of the following topics:

• Multi-agent models
• Reinforcement learning and other forms of associative learning
• Evolutionary and genetic algorithms
• Neuromorphic computing
• Spiking Neural Networks
• Deep Learning
• Game design
• Neuroeconomics and Computational Neuroscience

The fellowship will be for a period of three years, or alternatively, four years including 25% compulsory work (teaching and supervision activities or research administrative work). The decision on whether a 3 or a 4-year position is suitable will be discussed as part of the interview process. The academic work is to result in a doctoral thesis that will be defended at the Faculty to obtain the degree PhD.

• Master’s degree in computer science, computational neuroscience, electrical engineering or related fields (equivalent to 120 credits) with an average grade of A or B within a scale of A-E passing of grades
• Proficiency in both written and spoken English
• Documented education, research and/or work experience in at least one of the following fields Machine Learning, Artificial Life, or Robotics
• Experience programming in Python, Julia and/or C++

Admission to the doctoral program at the Faculty of Technology, Art and Design at OsloMet, within 3 months after employment in the position, is a prerequisite for joining the position. To be admitted to the PhD program, the applicant must have a B or better at the master's degree and C or better at the bachelor's degree. Candidates who already hold a PhD in the same or similar field may not apply. General criteria for appointments to academic positions are covered by the Forskrift om ansettelsesvilkår for stillinger som postdoktor, stipendiat, vitenskapelig assistent og spesialistkandidat.

• Experience researching Evolutionary Computation, Deep Learning and/or Reinforcement Learning
• Relevant published scientific publications

• The ability to finish tasks
• Motivation for contribution in the field of research
• Have an ability to work in an interdisciplinary group with diverse background
• Ability to work systematically and proactively
• An interest and ability to collaborate with other researchers

It is important to OsloMet to reflect the population of our region, and all qualified candidates are welcome to apply. We make active endeavors to further develop OsloMet as an inclusive workplace and to adapt the workplace if required. You are also welcome to apply for a position with us if you have experienced periods where you have not been in work, education or training.

An expert committee will assess the applications. You must upload the following documents with the application within the final date for applications:

• Application letter, describing your motivations for applying to this fellowship as well as a short overview of the qualifications, technical skills, experience, and personal skills that make you an attractive candidate for a successful and productive completion of this work.
• CV and copies of certificates/diplomas. The certificates/diplomas must include ECTS grades (A– F). Foreign diplomas must be translated into English by the degree-conferring institution. Education taken abroad should preferably be recognised in advance by NOKUT, and a confirmed copy of the letter of recognition should be enclosed.
• Names and contact details of 2-3 references (name, relation to candidate, email, and telephone number).
• Master's thesis (and any other scholarly work that the expert committee should take into consideration) must be submitted prior to signing of the contract.
• Applicants from countries where English is not the first language must present an official language test report. The following tests qualify as such documentation: TOEFL, IELTS, Cambridge Certificate in Advanced English (CAE) or Cambridge Certificate of Proficiency in English (CPE). Minimum scores are:

• TOEFL: 600 (paper-based test), 92 (Internet-based test)
• IELTS: 6.5, with no section lower than 5.5 (only Academic IELTS test is accepted)

The following applicants are exempt from the above-mentioned language requirements:

• Applicants from EU/EEA countries.
• Applicants who have completed one year of university studies in Australia, Canada, Ireland, New Zealand, the UK or USA.
• Applicants with an International Baccalaureate (IB) diploma.

We only process applications sent via our electronic recruitment system and all documents must be uploaded for your application to be processed. The documents must be in either English or a Scandinavian language. Translations must be authorized. Originals must be presented if you are invited for an interview. OsloMet performs document inspections in order to give you as a candidate a proper evaluation and ensure fair competition.

• An exciting job opportunity at Norway’s third largest and most urban university
• Opportunities for professional development in the AI Lab and within one of OsloMet’s Centers of Research Excellence, NordSTAR
• Beneficial pension arrangements with the Norwegian State Pension Fund
• Good employee welfare arrangements
• Free Norwegian classes to employees
• Working location in downtown Oslo with multiple cultural offers

Practical information about relocation to Oslo and living in Norway.

If you would like more information about the position, feel free to contact the supervision team:

• Associate Prof. Gustavo Moreno e Mello, [email protected]
• Professor Anis Yazidi, [email protected]
• Professor Stefano Nichele, [email protected]

The salary for the position is in accordance with the pay scale for Norwegian state employees, job title and position code. State salary wage scale 54, NOK 501 200 per year.The engagement is to be made in accordance with the regulations in force concerning State Employees and Civil Servants, and the acts relating to Control of the Export of Strategic Goods, Services and Technology. OsloMet has adhered to the principles in the DORA declaration and obliged the institution to follow the recommendations in this declaration.If you would like to apply for the position, you must do so electronically through our recruitment system.

Deadline for application: 15.12.2022Ref.: 22/07451

OsloMet is a Charter & Code certified institution by the EU Commisson holding the right to use the logo HR Excellence in Research (HRS4R). OsloMet is a member of the EURAXESS network supporting a positive work environment for researchers in motion. OsloMet has signed The Declaration on Research Assessment (DORA) . DORA recognizes the need to improve the ways in which the outputs of scholarly research are evaluated.  

Type of employment:

Fixed-term post

Contract type:

Full time

First day of employment:

--

Salary:

--

Number of positions:

1

Working hours:

100

City:

Oslo

County:

--

Country:

Norway

Reference number:

22/07451

Contact:

Gustavo Moreno e Mello, +4767237964

Published:

26/10/2022

Last application date:

15/12/2022 23:59