Salary: Up to £40157 Contract Type: Fixed Term - 18 Months Release Date: Thursday 17 November 2022 Closing Date: Tuesday 20 December 2022 Interview Date: Monday 09 January 2023 Reference: 3604
The European Union Marie Skłodowska-Curie Actions (MSCA) Industrial Doctorate programme MIcroelectronics RELiability driven by Artificial Intelligence (MIRELAI) is looking for talented and motivated Doctoral Candidates (DCs) with the skills, knowledge, and enthusiasm to help the industry-academia network make significant research breakthroughs. MIRELAI targets to address key strategic challenges faced by the microelectronics industry for delivering the next generation of reliable electronic components and systems (ECS).
The DCs will be part of a strong expert network and through interactions and collaborations will work towards joint project objectives. Shared hosting and joint supervision by the industry and academia of each of the 13 doctoral candidate projects targets an optimal training and knowledge transfer within the partnership. DCs will enrol in PhD degree programmes and be employed for 36 months by the respective academic-industrial partnership project, in a network composed of 14 beneficiaries and 7 associated partners from 7 European countries. For more details visit the official programme website at https: // mirelai.eu.
The DC project “Microstructure Informed Modelling and AI for Reliability Predictions” is undertaken in collaboration with MCS Ltd and offers a prestigious three-year MSCA PhD programme aimed at a novel approach for reliability along the electronic components and systems value chain. The successful candidate will benefit from an international scientific network of academic and industrial partners with research and training excellence in microelectronics reliability.
The research will focus on a new microstructure-informed reliability prediction approach for microelectronics packaging and component assembly designs based on:
1) Combination of state-of-the-art metrology and failure characterization methods and physics-of-failure modelling and machine learning methods.
2) Diagnosis of the electronics assembly's current health and prognosis of how degradation will progress over time.
Required documents: Complete applications in English should include: CV and copy of diploma , Letter of motivation, Letter of recommendation, English language proficiency certificate(s) (for applicants from non-majority English speaking countries).
The application dossier to be submitted as a single PDF file to firstname.lastname@example.org by the closing date for applications 20-12-2022. Please indicate in the subject line: ‘MIRELAI: PhD position 10 - your name‘
Shortlisted candidates will be invited for interviews by 09-01-2023.
For informal discussions about this role please contact Dr Stoyan Stoyanov on email@example.com
Further details: Job Description & Person Specification