|asque Center for Applied Mathematics is offering a Postdoctoral position in Modelling the Remaining Useful Lifetime for Offshore Wind Energy Technologies. This work is framed in IA4TES – Inteligencia Artifical para la Transición Energética Sostenible project. This offer, in particular, is to work in Computational Mathematics area at Basque Center for Applied Mathematics - BCAM, where Machine Learning, Data-Driven Computing, Numerical Simulation, Degradation Models, Transfer Learning, Offshore Wind Energy topics will be worked. |
Requirements: Applicants must have their PhD completed before the contract starts. PhD in Mathematics and/or Civil, Mechanical, Industrial, Offshore Engineering or similar areas
Skills: Good interpersonal skills. A proven track record in quality research, as evidenced by research publications in top scientific journals and conferences. Demonstrated ability to work independently and as part of a collaborative research team. Ability to present and publish research outcomes in spoken (talks) and written (papers) form. Ability to effectively communicate and present research ideas to researchers and stakeholders with different backgrounds. Fluency in spoken and written English.
The preferred candidate will have: Experience in reliability modelling of the remaining useful life for components/subsystems/systems using Bayesian approaches. Experience in degradation modelling. Experience in machine learning techniques and in particular in Transfer Learning problems. Experience in treatment of long time series. Experience in simulation of long time series. Good programming skills in Python and R. Interest and disposition to work in interdisciplinary groups.
The candidate would preferably be in possess of: Experience in the sector of offshore wind energy, or offshore oil and gas, or structures in offshore environment.