Industrial PhD-AI Training and Deployment under Sec Constraints
Saab AB / Datajobb / Göteborg
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About
The PhD position is part of an industrial collaboration between Saab AB, Software Center at Chalmers University of Technology and University of Gothenburg, and WASP (Wallenberg AI, Autonomous Systems and Software Program).
Your role
Successful machine- and deep-learning models require large amounts of data from real-world deployments for training and validation purposes. In some cases, such as in the defense industry, collecting this data to a central location is unfeasible or undesirable because of security and confidentiality reasons, excessive communication cost, or other reasons.
In addition, a centrally trained model may not suit all customers as different customers may have significantly varying contexts and circumstances and, consequently, want their ML/DL model deployment to be optimized for their specific situation with a reduced amount of data.
Conceptually, we would want a situation where a model can be trained up to some extent
centrally using the available data, then the model is deployed to all customers and locally trained based on customer data and then the learnings of all the deployed models are made available again centrally. This would allow us to build a solution where all customers are enjoying continuously improving systems by sharing their learnings with each other and receiving the combined learnings in updated ML/DL models. And all of this while maintaining confidentiality, limiting communication cost and allowing for customization of each system
deployment for specific customer needs.
From a more theoretical perspective, Transfer Learning (TL) provides part of the solution, but it only allows deployment of a centralized model to local contexts and training. To create
industrial strength, production-quality solutions, research is needed to address three main challenges:
We need solutions that support the merging of local training results with the central model without sacrificing confidentiality and security.
We need solutions that allow for the deployment of updated centrally trained models to customers who maintain the local customization that was trained into the previous deployment of the model.
We need to investigate the required engineering infrastructure, necessary ways of working (both internally and with customers) and deployment approaches that maintain the security requirements of defense customers.
Your profile
* Master's level degree corresponding to at least 240 higher education credits
* Very good verbal and written communication skills in Swedish and English
* Interest and skills in AI
* Interest and skills in SW development
This position requires that you will be approved in a security screening in accordance with the Swedish Protective Security Act.
Note: In order to start this Industrial cooperation between SAAB AB and Software Center at Chalmers University of Technology and University of Gothenburg, we have to apply for
funding for a named applicant. Regardless the outcome of this application, you will be
offered a position at Saab.
What you will be a part of
Surveillance, a Business Area within Saab, is a world-leading supplier of systems for detection of threats and self-protection. Business Unit Radar Solutions is responsible for Radar in airborne-, surface- and naval systems. This position will be organized within our Innovation Lab.
If you aspire to help create and innovate whilst developing yourself in a challenging team
setting, Saab may well have the perfect conditions for you to grow. We pride ourselves on a nurturing environment, where everyone is different yet we share the same goal - to help
protect people.
For questions, please contact:
Ulf Näsström, Recruiting Manager
• 46 734 379 051
Sven Nilsson, Technical Specialist
• 46 734 379 410
Åsa Mårtensson, HR Specialist Recruitment
• 46 10 2165107
Varaktighet, arbetstid
Heltid Contract
Publiceringsdatum2020-02-27ErsättningNot Specified
Så ansöker duSista dag att ansöka är 2020-03-19
Klicka på denna länk för att göra din ansökanFöretagSAAB AB
Arbetsgivarens referens Arbetsgivarens referens för detta jobb är "REQ_03797".
Omfattning Detta är ett heltidsjobb.
Arbetsgivare Saab AB (org.nr 556036-0793)
Arbetsplats Saab AB
Jobbnummer 5120742
Observera att sista ansökningsdag har passerat.