Research Engineer in Machine learning - Deep learning
|Workplace||Stockholm, Södermanland, Sweden|
Apply for position
School of Electrical Engineering and Computer Science at KTHKTH 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 descriptionAt the Division of Computational Science and Technology at KTH Royal Institute of Technology we are developing deep learning methods that handle scaling transformations in image data in a theoretically well-founded manner, see ?url=https%3A%2F%2Fwww.kth.se%2Fprofile%2Ftony%2Fpage%2Fdeep-networks&module=jobs&id=2320497" target="_blank" rel="nofollow">?url=https%3A%2F%2Fwww.kth.se%2Fprofile%2Ftony%2Fpage%2Fdeep-networks&module=jobs&id=2320497" target="_blank" rel="nofollow">https://www.kth.se/profile/tony/page/deep-networks for examples of our earlier work.
We are seeking a research engineer to participate in this research by developing new network architectures and perform systematic experiments with these. The work comprises generating data sets that test scaling variations in testing data that are not spanned by training data, and investigating how other prior knowledge to the networks can make them generalise to new scales that are not spanned by the training data.
As requirements to the position, you are expected to have good knowledge of and being able to work independently with modern networks for deep learning, preferably PyTorch.
You are also expected to have good basic knowledge in mathematics to model convolution operations on continuous image data. A suitable background could be studies in engineering physics or computer science.
The work can be done full time or part time, according to agreement. The employment is to last 3 months but there might be possibilities for prolongation
What we offer
Read more about what it is like to work at KTH
Knowledge and skills that are meritorious for the position
As a person, you have good knowledge in structured programming in Python, preferably in PyTorch. Furthermore, you should have good collaboration skills in combination with independence, with very good ability to familiarize yourself with new scientific theories and conduct implementations and experimental evaluations in close collaboration with the research environment you are working in. Awareness of diversity and equal opportunity issues, with specific focus on gender equality is also important.
Great emphasis will be placed on personal competency.
Trade union representativesYou will find contact information to trade union representatives at KTH’s webbpage .
ApplicationLog 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.
The application must include:
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 employmentThe employment is valid for a limited time according to the agreement - for up to 3 months, with access according to agreement.
Striving towards gender equality, diversity and equal conditions is both a question of quality for KTH and a given part of our values
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.
Type of employment
Temporary position 3-6 months
First day of employment
According to agreement
Number of positions
Last application date
22.Aug.2022 11:59 PM CEST
Apply for position
In your application, please refer to myScience.org and reference JobID 2320497.
2 August 2022
Using smartphones could help improve memory skills
» More news