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  Dr Stoyan Stoyanov  No more applications being accepted  Funded PhD Project (Students Worldwide)

About the Project

MIRELAI project doctorate researcher

School of Computing & Mathematical Sciences

Greenwich Campus

Up to £40,157

Fixed Term Contract - 18 Months

Ref: 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

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.

Project description

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 [Email Address Removed] by the closing date for applications 22-01-2023. Please indicate in the subject line: ‘MIRELAI: PhD position 10 - your name‘

Closing Date: 22nd January 2023

Interview Date: 29th January 2023

If you are interested in this role then please click this link for more information and to apply:

For informal discussions about this role please contact Dr Stoyan Stoyanov at [Email Address Removed]

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