Research Associate in Space Computational Intelligence (597996)
| Posting date: | 24 April 2024 |
|---|---|
| Salary: | £36,024 to £44,263 per year |
| Hours: | Full time |
| Closing date: | 14 May 2024 |
| Location: | Glasgow, Scotland |
| Remote working: | Hybrid - work remotely up to 1 day per week |
| Company: | University of Strathclyde |
| Job type: | Contract |
| Job reference: | 597996 |
Summary
Salary range: £36,024 - £44,263 per annum
FTE 1.0
Term: Fixed (12 Months)
Closing date: 14 May 2024
The Faculty of Engineering at the University of Strathclyde is one of the largest and most successful engineering faculties in the UK, and the largest in Scotland. As a leading international technological university, Strathclyde is recognised for its world class research, knowledge exchange and educational programs. At the heart of this is the Faculty of Engineering which boasts a growing research portfolio of over £85 million.
The Department of Mechanical & Aerospace Engineering is the birthplace of modern engineering education, informing the technology leaders of today and tomorrow since 1800. Our mission is to advance knowledge and commerce in mechanical and aerospace engineering, and apply fresh thinking to the challenges faced by industry and society.
The Aerospace Centre of Excellence in the Department of Mechanical & Aerospace Engineering seeks to appoint a Post-doctoral Research Associate in Computational Intelligence to work on projects supported by the European and UK Space Agencies (ESA and UKSA). The successful candidate will work on Natural Language Processing for Explainable AI with application to space safety and sustainability.
To be considered for the role, you will be educated to a minimum of Master degree level in a discipline related to Engineering, Physics, Mathematics or Computer Science and have obtained or about to obtain a PhD in the same area with application to deep learning. You will have experience in one or more of the following areas: machine learning, generative deep learning, dynamical system theory, uncertainty quantification. You will have the ability to develop and deliver research activities, and work on collaborative projects involving both industry and academia. You will be ambitious and enthusiastic about cross-disciplinary working and be able to work independently and as part of a team, supporting others when required. You will have good interpersonal and communication skills, including an ability to listen, engage and persuade, and to present complex information in an accessible way to a range of audiences. You will have the ability to work well under pressure and be driven to deliver results. The appointment will be made at Research Associate level.
For informal enquiries, please contact Massimiliano Vasile on massimiliano.vasile@strath.ac.uk
Previous applicants need not apply.
FTE 1.0
Term: Fixed (12 Months)
Closing date: 14 May 2024
The Faculty of Engineering at the University of Strathclyde is one of the largest and most successful engineering faculties in the UK, and the largest in Scotland. As a leading international technological university, Strathclyde is recognised for its world class research, knowledge exchange and educational programs. At the heart of this is the Faculty of Engineering which boasts a growing research portfolio of over £85 million.
The Department of Mechanical & Aerospace Engineering is the birthplace of modern engineering education, informing the technology leaders of today and tomorrow since 1800. Our mission is to advance knowledge and commerce in mechanical and aerospace engineering, and apply fresh thinking to the challenges faced by industry and society.
The Aerospace Centre of Excellence in the Department of Mechanical & Aerospace Engineering seeks to appoint a Post-doctoral Research Associate in Computational Intelligence to work on projects supported by the European and UK Space Agencies (ESA and UKSA). The successful candidate will work on Natural Language Processing for Explainable AI with application to space safety and sustainability.
To be considered for the role, you will be educated to a minimum of Master degree level in a discipline related to Engineering, Physics, Mathematics or Computer Science and have obtained or about to obtain a PhD in the same area with application to deep learning. You will have experience in one or more of the following areas: machine learning, generative deep learning, dynamical system theory, uncertainty quantification. You will have the ability to develop and deliver research activities, and work on collaborative projects involving both industry and academia. You will be ambitious and enthusiastic about cross-disciplinary working and be able to work independently and as part of a team, supporting others when required. You will have good interpersonal and communication skills, including an ability to listen, engage and persuade, and to present complex information in an accessible way to a range of audiences. You will have the ability to work well under pressure and be driven to deliver results. The appointment will be made at Research Associate level.
For informal enquiries, please contact Massimiliano Vasile on massimiliano.vasile@strath.ac.uk
Previous applicants need not apply.
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