Doctoral Candidate #6
Project title: Discovery of bimetallic catalysts via machine learning algorithms.
Project objectives: This PhD project will involve the development, optimisation, and benchmarking of machine learning models to predict the binding energies of key CO2RR intermediates using the thermodynamic data calculated by other partners or taken from the literature.
Expected outcome: The main outcome of this PhD project would be a machine learning model able to predict binding energies of key CO2RR intermediates while exhibiting a comparable accuracy to state-of-the-art density functional theory methods. The developed machine learning model will be used to screen for novel Cu-based materials (and possibly other bimetallic alloys) for the CO2RR.
Working context: DC#6 will be hosted and supervised by Prof. M. García-Melchor in Trinity College Dublin (Ireland). DC#6 will enrol in the PhD programme (DubChem) of the same institution and receive the necessary training via the courses offered therein and the TCD team. Complementary training in the modelling of the reaction thermodynamics and kinetics of the CO2RR on metallic surfaces will also be provided via secondments at POLITO and UI, respectively. In addition, part of the proposed activities will be carried out via secondment periods at TME to expand DC#6’s knowledge of machine learning.
Specific requirements and eligibility criteria of the PhD School of the Trinity College Dublin. The applicant will need to:
- Hold at least a 2.1 honors degree in Chemistry, Physics, Nanoscience, Chemical Engineering, or related discipline, from an Irish university or equivalent result from a university in another country.
- Display a high level of competence in the English language in one of the examination systems recognised by Trinity College Dublin.
Post graduate English language requirements. All applicants whose first language is not English and who have not been educated through the medium of English must present one of the following qualifications in the English language:
- IELTS: Grade 6.5 overall
- TOEFL: 88 internet-based, 570 paper-based, 230 computer-based
- University of Cambridge:
Proficiency Certificate, Grade C or better (CEFR Level C1 or C2)
Advanced Certificate, Grade C or better (CEFR Level C1 or C2) - Pearson Test of English (Academic) – PTE Academic: a minimum score of 63 to be eligible (with no section score below 59)
- Duolingo English Test: minimum overall score of 110/160, dated since January 2020
- An award certificate with a minimum II.1 overall score from Trinity’s Centre for English Language Learning and Teaching’s Pre-Master’s Pathway Programme. The Pre-Master’s Pathway Programme is an academic English course for international students with conditional offers for postgraduate study at Trinity. Passing the programme means you meet Trinity’s English language requirement and can progress to your postgraduate course without retaking IELTS or any other exam.
The Pre-Master’s Pathway Programme is an academic English course for international students with conditional offers for postgraduate study at Trinity. Passing the programme means you meet Trinity’s English language requirement and can progress to your postgraduate course without retaking IELTS or any other exam.
Please also note that existing IELTS, TOEFL, Cambridge and PET scores up to two years old will be accepted for 2021/22 applications in light of test centre closures.
For further details on these English Language Proficiency Tests, please contact the appropriate organisation directly.
An applicant whose first language is not English but who has taken a degree through the medium of English may be eligible. However some courses may request applicants to present an English Language qualification under certain circumstances.
Starting date and contract duration: The contract will start no later than the 1st of November 2023 and will last 36 months.
For further information on this position please contact Prof. M. García-Melchor (email: garciamm@tcd.ie).
All details on ECOMATES’s open positions are also reported on the Euraxess portal at the link https://euraxess.ec.europa.eu/jobs/44519.
