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Open Position at LCRS-CNRS in collaboration with ICMAB: Battery materials for “Internet of Things” sensors

Deadline: Jul 31, 2021

The LCRS-CNRS, ICMAB, and Cambridge University are looking for a candidate to do a PhD around the development of new high capacity battery chemistries operating at low voltages (0.7-1.2V) that are suitable for powering IoT autonomous sensors.

Artur
Jun 22, 2021
Electronic components for the Internet of Things / Robin Glauser

The LCRS-CNRS Laboratory at the Université de Picardie Jules Verne (France), the Institut de Ciència de Materials de Barcelona (ICMAB-CSIC, Spain), and Cambridge University (UK) jointly invite applications for a three-year PhD project entitled:

Battery materials for “Internet of Things” sensors: machine-learning guided discovery, synthesis, characterization and testing

This PhD proposal deals with the development of new high capacity battery chemistries operating at low voltages (0.7-1.2V) that are suitable for powering IoT autonomous sensors.

The research work will be based on a dual approach involving first discovery of new materials via an artificial intelligence (Machine-Learning) approach (1st year) followed by synthesis and characterization of such compounds, involving operando experiments, and final integration in coin-cell battery prototypes and testing.

The research project will be co-supervised by Prof. Alejandro Franco (LRCS), Prof. M. Rosa Palacin (ICMAB-CSIC) and Prof. Clare Grey (Cambridge University) and will involve mobility within the 3 laboratories.  The work will be carried out in the framework of the ALISTORE European Research Institute and hence the student is expected to attend ALISTORE ERI bi-annual meetings which have the participation of both academic and industrial club members, and present the results achieved.   

The candidate will be employed by CNRS or a period of up to three years, with a gross salary of 2135 €/month and registered at the UPJV Doctoral School.

Tentative starting date: fall 2021

Applicants should have a degree from a relevant Master course (Solid state chemistry and physics, Inorganic materials for Energy Storage and Conversion, Electrochemistry of materials…). Academic knowledge of solid state chemistry, electrochemistry and machine learning methods will be highly appreciated as well as good communication skills, team spirit, and interest in interdisciplinary topics. 

Deadline

Application period will be closed once a suitable candidate is found. 

Contact information

  • Alejandro A. Franco (This email address is being protected from spambots. You need JavaScript enabled to view it.)
  • M. Rosa Palacin (This email address is being protected from spambots. You need JavaScript enabled to view it.)
  • Clare Grey (This email address is being protected from spambots. You need JavaScript enabled to view it.)

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