Doctoral student in brain-like machine intelligence and artificial cognition

Project description

Third-cycle subject: Computer Science with specialisation in Computational Biology

This position offers a unique opportunity to develop and advance cognitive brain theories and build computational neural network models to inform the emerging class of brain-inspired AI systems towards brain-like machine intelligence. The successful applicant will capitalise on the vibrant interdisciplinary environment sustained by a strategic collaborations with Karolinska Institute and Stockholm University.

The goal of the project is to develop and simulate large-scale neural network models of the brain’s cognitive function with focus on cortical memory system, and use them to make advances towards brain-like intelligent systems. Special focus is on coupling multiple neural networks to study neural interactions between different cortical regions supporting cognitive function. You are expected to build such large-scale brain plausible network-of-networks models in the continuum between spiking and non-spiking computations, and hence propose novel architectural blueprint for AI agents. You should also be able to evaluate the emerging models given multi-modal data and constraints. The project will involve interdisciplinary efforts across multiple fields including cognitive science, computational neuroscience, machine learning / AI (deep generative modelling) and dynamical systems among others.

The position also implies the need to write scientific papers in English.

Supervision: Pawel Herman is proposed to supervise the doctoral student. Decisions are made on admission

Admission requirements

To be admitted to postgraduate education (Chapter 7, 39 § Swedish Higher Education Ordinance), the applicant must have basic eligibility in accordance with either of the following:

• passed a second cycle degree (for example a master's degree), or
• completed course requirements of at least 240 higher education credits, of which at least 60 second-cycle higher education credits, or
• acquired, in some other way within or outside the country, substantially equivalent knowledge.
• The applicant's degree education is expected to be in the field of computer science, engineering physics/math, cognitive science or related areas.

In addition to the above, there is also a mandatory requirement for English equivalent to English B/6.

Selection

In order to succeed as a doctoral student at KTH you need to be goal oriented and persevering in your work. During the selection process, candidates will be assessed upon their ability to:

• independently pursue his or her work
• collaborate with others,
• have a professional approach and
• analyze and work with complex issues.
• In addition, interest in brain’s cognitive function, computational brain theories as well as cortical computations is particularly appreciated.
• Also, competence in scientific programming, numerical simulations or GPU programming is desirable, but not mandatory.
• Finally, previous experience in large-scale neural network based brain models (spiking or non-spiking) is regarded as advantageous qualification.

After the qualification requirements, great emphasis will be placed on personal skills. 

Target degree: Doctoral degree

Information regarding admission and employment

Only those admitted to postgraduate education may be employed as a doctoral student. The total length of employment may not be longer than what corresponds to full-time doctoral education in four years' time. An employed doctoral student can, to a limited extent (maximum 20%), perform certain tasks within their role, e.g. training and administration. A new position as a doctoral student is for a maximum of one year, and then the employment may be renewed for a maximum of two years at a time. 

As a doctoral student, you are entitled to a workplace with many employee benefits and monthly salary according to KTH’s Doctoral student salary agreement. Read more about Doctoral studies (PhD) | KTH | Sweden.

Union representatives

Contact information for union representatives.

Doctoral Student’s network (Students’ union on KTH Royal Institute of Technology)

Contact information for PhD chapter.

To apply for the position

Apply for the position and admission through KTH's recruitment system. It is the applicant’s responsibility to ensure that the application is complete in accordance with the instructions in the advertisement.

Applications must include the following elements:

• Copies of diplomas and grades from previous university studies and certificates of fulfilled language requirements (see above). Translations into English or Swedish if the original document is not issued in one of these languages.Copies of originals must be certified.
• CV including your relevant professional experience and knowledge.
• Application letter with a brief description of why you want to pursue research studies, about what your academic interests are and how they relate to your previous studies and future goals. (Maximum 2 pages long)
• Representative publications or technical reports. For longer documents, please provide a summary (abstract) and a web link to the full text.

Applications must be received at the last closing date at midnight, CET/CEST (Central European Time/Central European Summer Time).

Other information

For information about processing of personal data in the recruitment process.

It may be the case that a position at KTH is classified as a security-sensitive role in accordance with the Protective Security Act (2018:585). If this applies to the specific position, a security clearance will be conducted for the applicant in accordance with the same law with the applicant's consent. In such cases, a prerequisite for employment is that the applicant is approved following the security clearance.

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Disclaimer: In case of discrepancy between the Swedish original and the English translation of the job announcement, the Swedish version takes precedence.

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Learn more about our benefits and what it's like to work and grow at KTH

1. Pawel Herman, [email protected]