Industrial Ph.D. - AI-driven product design automation
Ab SKF / Högskolejobb / Göteborg
2024-07-01
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hela Sverige Are you passionate about the intersection of artificial intelligence and mechanical engineering in a real-world setting? Then you could join SKF's Technology Development as...
Industrial Ph.D. - AI-driven product design automation
At SKF Technology Development, we strongly believe that introducing new technological advances in our current engineering processes can open new spaces for innovation. By evolving our solution space, we can better and faster tailor the correct solution to the customer's technical needs and requirements and create better products and processes for tomorrow.
In collaboration with Linnaeus University, SKF is looking for an industrial Ph.D. student to work on the topic of using artificial intelligence to automate engineering design and product development. The successful candidate will join a multidisciplinary team of researchers and engineers who are developing innovative solutions for the design and optimization of mechanical systems. The goal of the project is to apply state-of-the-art techniques to automate the design process of various components and products, such as bearings, seals, and lubrication. The project will involve both theoretical and practical aspects.
About the job
As an AI Industrial Ph.D. within this project, you will be at the forefront of leveraging the power of machine learning and AI and make an important contribution to advance our engineering and design approaches and enable engineers and designers to create better products and services across various industries.
You will work closely with our business leaders, product development community, and university to develop AI solutions that enhance design processes and services. You will be part of reinventing the current way of working by using new tools and technologies to drive towards the concept of Automated design.
About your tasks
explore and identify applicable data sources such as design rules, current designs, and testing data
analyze large amounts of data, both structured and unstructured
create new solutions and strategies for engineering problems
work with team members and leaders to develop a strategy to validate AI techniques
to discover trends and patterns, combine various algorithms and modules for engineering purposes
validate and pilot solutions using various techniques and tools
construction pilot solutions for the actual bearing design process
About you
To be successful in this role, we see that you have experience and/or education in the following topics:
mechanical engineering
statistical analysis and computing
machine learning
deep learning
large language modeling
processing large data set
data visualization
data wrangling
mathematics
programming
The industry Ph.D. student will be employed at SKF Technology Development located in Sweden (Gothenburg). Travel to Linnaeus University (Växjö) will be required. Additional periodical traveling might be required.
Requirements from Linnaeus University
The industry Ph.D. student will be enrolled in the graduate program at Linnaeus University's industry graduate school on Data Intensive Applications (DIA,
https://lnu.se/DIA). Therefore, the following academic requirements need to be fulfilled.
General entry requirements
has been awarded a second-cycle qualification
has satisfied the requirements for courses comprising at least 240 credits of which at least 60 credits were awarded in the second cycle or has acquired substantially equivalent knowledge in some other way in Sweden or abroad.
Specific entry requirements
approved courses of a minimum of 90 credits in the subject of Computer and Information Science or the equivalent
an individual study project of a minimum of 15 credits in the subject of Computer and Information Science, or the equivalent.
Assessment criteria
Good programming skills (for example Java, C#, Ruby, or Python), and solid training in mathematics and theoretical computer science. Documented expertise and working experience within at least two of the following research and educational areas is a great advantage:
Big data analytics
Data visualization
Machine learning
Predictive Maintenance
Parallel processing
Because of the interdisciplinary character of the project and LNUC DISA (
https://lnu.se/en/disa), the candidate should be an enthusiastic person who is interested in making sense of large and complex data sets of various types as well as capable of working both independently and within a group. Teamwork experience should be documented in the application. Professional proficiency in written and spoken English is required.
Start date: August 2024
Duration: 4-5 years
Location: Gothenburg, Sweden
Salary: According to SKF's regulations
Application
If you are interested and fulfill the criteria, please submit your application no later than July 12. Please include a cover letter, a CV, and a transcript of records in your application.
For questions about the Ph.D., please contact Linda Örtlund, Manager of Architecture, AI and Developmen Principles, at
linda.ortlund@skf.com.
For questions about the recruitment process, please contact Danijel Sjögren, Recruitment Expert EMEA, at
danijel.sjogren@skf.com.
Så ansöker du Sista dag att ansöka är 2024-07-12
Klicka på denna länk för att göra din ansökan Omfattning Detta är ett heltidsjobb.
Arbetsgivare AB SKF (org.nr 556007-3495)
Sven Wingquists Gata 2 (
visa karta)
415 26 GÖTEBORG
Jobbnummer 8779918