Machine Learning Researcher

Há 3 dias


Porto, Porto, Portugal Centre National De La Recherche Scientifique Tempo inteiro

Company Overview

The Centre National de la Recherche Scientifique (CNRS) is a leading research institution in France, dedicated to advancing knowledge and innovation in various fields. As part of its commitment to excellence, CNRS invites applications for a PhD position in Machine Learning-Based Inverse Design Of Synthesis Protocols.

Salary

The successful candidate will be offered a monthly gross salary of approximately 3048.29 €, including a mobility allowance.

Job Description

The advertised subproject is fully funded by the Marie Sklodowska-Curie European Training Network "PREDICTOR". It will be carried out by one doctoral candidate at the Laboratoire de Réactivité de Chimie des Solides -LRCS- (CNRS & Université de Picardie Jules Verne joint laboratory), in Amiens, France under the supervision of Prof. Dr. Alejandro A. Franco over a period of 36 months. The PhD candidate will be in charge of developing cutting-edge machine learning models correlating materials synthesis protocols with materials properties, and using such models in an innovative multi-objective Bayesian optimiser able to predict which synthesis protocols to adopt to reach the material property target.

Required Skills and Qualifications

The PhD candidate should have a strong background in Artificial Intelligence (AI) methods, including machine learning, and data science methods as a whole. Experience with Python programming language and classical AI libraries is necessary. The candidate should also have a background on computational modeling (e.g. elementary kinetic modeling, kinetic Monte Carlo) and knowledge on materials science and/or physical-chemistry of materials. Knowledge and/or experience in the field of batteries or redox flow batteries, as well as in the synthesis of materials for these technologies, will be appreciated.

Benefits

The recruited researcher will have the opportunity to work as part of an international, interdisciplinary team of 17 doctoral candidates, based at universities and industrial firms throughout Europe. She/he will be supported by two mentors within the PREDICTOR project, and will have multiple opportunities to participate in professional and personal development training. Through her/his work she/he will gain a unique skill-set at the interface between modelling and simulation, high-throughput experimentation/characterization and self-optimization and data management over different length scales from nano to the macroscopic level.

Others

The applicant must not have resided or carried out her/his main activity (work, studies etc.) in France for more than 12 months in the past 3 years. An earlier starting date is possible if preferred.



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