Here is an interesting PhD open position for a data science expert at
Total group
(Total, a major energy player ) in
partnership with Institut Elie Cartan de Lorraine at Nancy, France and
SAFT at Bordeaux, France
Subject : Statistical modelling and uncertainty analysis of battery
lifetime.
======Industrial context===
In a global context to reduce the energy consumption and the carbon
footprint in order to
fight against the climatic change, a lots of efforts are engaged in
particular in transportation with
electrification of vehicle and in the energy production with more and
more renewable like solar or
wind. In this context part of Lithium-Ion batteries in the modern energy
management solutions
are quickly growing and is becoming one of the critical components in
modern electric vehicles
or in energy storage solution. However, the cost of such battery remains
important in the overall
system. In addition the battery performances degrades as long as the
battery is used. Indeed,
the accurate prediction of how fast the battery will degrade and then
how long the battery will
be able to be used in the system before having to be replaced is
critical. This critical knowledge
should avoid to over-size the battery and so is a key advantage for a
battery supplier for its
competitiveness. Such prediction are adressed today by models which
require a lot of intensive
tests. In addition the determination of the uncertainty of such model is
a key information for
battery company to assess the financial risk for commercial bids where
they are engaged on the
battery lifetime. The goal of the PhD thesis is to develop machine
learning methods to estimate
in the same way the lifetime of a battery as well as the associated
uncertainty.
Saft is a world leader in batteries for lots of different markets and is
part of group Total
which has the ambition to become one of the major company in energy.
Recently Saft and Total
has announced an alliance in particular with PSA to create an European
company to adress the
volume market of batteries for electrical vehicle in order to help
Europe to be competitive and
independant against Asian compagnies.
=====Profile=============
The ideal candidate is strongly motivated by environmental questions,
passionate about artificial intelligence and engineering, has a solid
background in applied mathematics, statistics,
and has good scientific writing skills. A proven experience and taste
for computer programming
and data analysis is required.
Candidates should hold a MSc in Computer Science, Applied Mathematics,
Engineering or
related fields. A strong command of English language is also required.
=====Application===========
Application files must be sent to :
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— A cover letter or email,
— A CV, including contact information for two or more referees
— A research outcome (Master’s thesis or paper) written by the candidate
— A transcript of grades
Incomplete application files will not be considered.
