Om jobbet
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Denna position rapporterar till:
R&D Team Lead
This thesis aims to develop remote/safe learning-based control framework for the application of underground mining operations.
Traditional control strategies face significant challenges due to uncertain dynamics, high safety risks, remote operations and the need for autonomous operations in constrained and hazardous conditions. We aim to design and validate a learning-based controller that not only learns optimal strategies but also integrates safety constraints and uncertainties to prevent unsafe actions.
By incorporating risk-sensitive policies, and safe exploration techniques, reliability and operational safety will be guaranteed.
Details
Your role and responsibilities
Develop remote & risk-aware control algorithms considering safety constraints to ensure reliable and secure operations in uncertain and hazardous mining conditions and consider delays between controller and plant which deteriorates the control efficiency.
In this regard, the state of the art for remote control solutions with learning uncertainties and safety guarantees will be reviewed, the appropriate safety guaranteed control algorithm are designed and the performance of the solution will be evaluated via numerical simulations.
Approach
The work will address the following points:
Qualifications for the role
More about us
Supervisor Maryam Sharifi, maryam.sharifi@se.abb.com, and Alf Isaksson, alf.isaksson@se.abb.com, will answer all your questions about the thesis topic and expectations. Recruiting Manager Linus Thrybom, +46 730 80 99 06, will answer your questions regarding hiring.
Positions are filled continuously. Please apply with your CV, academic transcripts, and a cover letter in English. We look forward to receiving your application!
Kommande möjligheter Vänligen notera att denna annons syftar till att få in intresseanmälningar till en kandidatpool kopplat till det aktuella området, och det är därför inte en öppning till ett specifikt jobb just nu. Genom att ansöka uttrycker du ditt intresse för framtida karriärmöjligheter med ABB.
Vi värdesätter människor med olika bakgrund. Ansök idag för att ha möjlighet att bli aktuell för kommande roller och besök www.abb.com för att utforska hur vi driver utveckling över hela världen.
Denna position rapporterar till:
R&D Team Lead
This thesis aims to develop remote/safe learning-based control framework for the application of underground mining operations.
Traditional control strategies face significant challenges due to uncertain dynamics, high safety risks, remote operations and the need for autonomous operations in constrained and hazardous conditions. We aim to design and validate a learning-based controller that not only learns optimal strategies but also integrates safety constraints and uncertainties to prevent unsafe actions.
By incorporating risk-sensitive policies, and safe exploration techniques, reliability and operational safety will be guaranteed.
Details
- Period: 5 months in 2026 (January/February - June/July)
- Number of credits: 30 ECTS
- Number of students for this thesis work: 1-2
- Location: ABB Research Center in Västerås
- ABB may cover the accommodation in Västerås
Your role and responsibilities
Develop remote & risk-aware control algorithms considering safety constraints to ensure reliable and secure operations in uncertain and hazardous mining conditions and consider delays between controller and plant which deteriorates the control efficiency.
In this regard, the state of the art for remote control solutions with learning uncertainties and safety guarantees will be reviewed, the appropriate safety guaranteed control algorithm are designed and the performance of the solution will be evaluated via numerical simulations.
Approach
The work will address the following points:
- Problem formulation
- Prior art review
- Method & solution development
- Validation by simulation/experiments
Qualifications for the role
- Strong background in machine learning, control, computer science, or similar disciplines
- Motivated to solve real-world problems using state-of-the-art methods
- Self-driven and solution oriented
- Good programming skills (Python/MATLAB)
More about us
Supervisor Maryam Sharifi, maryam.sharifi@se.abb.com, and Alf Isaksson, alf.isaksson@se.abb.com, will answer all your questions about the thesis topic and expectations. Recruiting Manager Linus Thrybom, +46 730 80 99 06, will answer your questions regarding hiring.
Positions are filled continuously. Please apply with your CV, academic transcripts, and a cover letter in English. We look forward to receiving your application!
Kommande möjligheter Vänligen notera att denna annons syftar till att få in intresseanmälningar till en kandidatpool kopplat till det aktuella området, och det är därför inte en öppning till ett specifikt jobb just nu. Genom att ansöka uttrycker du ditt intresse för framtida karriärmöjligheter med ABB.
Vi värdesätter människor med olika bakgrund. Ansök idag för att ha möjlighet att bli aktuell för kommande roller och besök www.abb.com för att utforska hur vi driver utveckling över hela världen.
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