
30 Nov Research Engineer in Machine Learning and Neuroscience
KTH Royal Institute of Technology, School of EECS
KTH Royal Institute of Technology in Stockholm has grown to become one of Europe’s leading technical and engineering universities, as well as a key centre of intellectual talent and innovation. We are Sweden’s largest technical research and learning institution and home to students, researchers and faculty from around the world. Our research and education covers a wide area including natural sciences and all branches of engineering, as well as architecture, industrial management, urban planning, history and philosophy.
Job description
The Division of Robotics, Perception, and Learning (RPL) at KTH (https://www.kth.se/rpl) is looking for students interested in getting hands-on research experience in the area of Machine Learning and Neuroscience.
What we offer
- A position at a leading technical university that generates knowledge and skills for a sustainable future.
- Engaged and ambitious colleagues along with a creative, international, and dynamic working environment.
- Work in Stockholm, in close proximity to nature.
- In addition to a faculty advisor, each chosen candidate will be matched with a technically relevant researcher (e.g. Ph.D. student or postdoc) who will serve as the candidate´s research collaborator and mentor.
- The possibility to interact with a diverse team of researchers with high ambitions in an open, curious, and dynamic environment.
- Participation in the group activities of the division.
Read more about what it is like to work at KTH
Qualifications
Requirements
The candidate should be enrolled in a master’s degree in computer science, neuroscience, machine learning, computer engineering, electrical engineering, mathematics, robotics, computer vision, or similar.
- Excellent software development and integration skills, preferably in Python and C++/C#.
- Solid mathematical background.
- Familiarity with deep learning algorithms and tools, as well as techniques in neuroscience to clean EEG signals and remove artifacts.
- Excellent writing and communication skills.
Preferred qualifications
- Experience with projects (e.g. at course level) related to Machine Learning and Neuroscience is of preference.
Candidates applying for this position are comfortable working in groups as well as independently, and you have a good sense of structure in your daily work tasks.
Great emphasis will be placed on personal competence and suitability.
Trade union representatives
You will find contact information to trade union representatives at KTH’s webbpage.
Application
The application must include:
- CV including relevant project experience and knowledge.
- Copy of diplomas and grades from university studies. Translations into English or Swedish if the original documents have not been issued in any of these languages.
- Brief account (maximum one page) of how this position is relevant for you and can contribute to your future academic career.
Log into KTH’s recruitment system in order to apply to this position. You are the main responsible to ensure that your application is complete according to the ad.
Your complete application must be received by KTH no later than the last day of application, midnight CET/CEST (Central European Time/Central European Summer Time).
About the employment
Temporary employment for up to 6 months, or by agreement.
The employment is valid indefinitely or is limited by agreement.
Other information
Gender equality, diversity and zero tolerance against discrimination and harassment are important aspects of KTH’s work with quality as well as core values in our organization.
For information about processing of personal data in the recruitment process please read here.
We firmly decline all contact with staffing and recruitment agencies and job ad salespersons.
Disclaimer: In case of discrepancy between the Swedish original and the English translation of the job announcement, the Swedish version takes precedence.
Additional Info:
Type of employment : Temporary position 3-6 months
Employment expires : 2021-06-30
Contract type : Full time
First day of employment : In agreement with supervisor
Salary : Monthly salary
Number of positions : 1
Working hours : 100%
City : Stockholm
County : Stockholms län
Country : Sweden
Reference number : J-2020-2416
Contact : Sarah Kullgren, HR, sarahku@kth.se, Ali Ghadirzadeh, Supervisor, algh@kth.se
Published : 29.Oct.2020
Last application date : 15.Dec.2020 11:59 PM CET
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