[CvGmt News] Fwd: Call for application to a Marie Curie PhD position. Deadline 15 May.

[Giuseppe Buttazzo]

-------- Original Message --------
Subject: Fwd: Call for application to a Marie Curie PhD position. 
Deadline 15 May.
Date: 03-05-2018 17:15
 From: Mohamed Masmoudi <masmoudi at adagos.com>
To: buttazzo at dm.unipi.it
Reply-To: masmoudi at adagos.com

Dear Giuseppe ,
I hope that you are doing well.

As you may know, I am in charge of ADAGOS a spinoff of the Institute of
Mathematics of Toulouse. We have the chance to participate in a European
Project.
In the frame of this project, I am looking for a PhD student. The topic
is described below.
To be eligible for this position, the candidate must not have resided in
France for more than 12 months over the last three years.
For this reason, I am asking for your assistance.

Please could you recommend a good student or spread this information
around you.
Best wishes,
M.

TITLE: STATISTICAL SHAPE MODELLING AND REDUCED ORDER MODELLING
TECHNIQUES FOR PATIENT-SPECIFIC MODELSMore information can be found on:

https://spinner-eid.eu/

https://spinner-eid.eu/spinner-spine-numerical-and-experimental-repair-strategies/

Start Date: 01-September-2018
Host Institution: ADAGOS [1], France
Academic Institution: University of Sheffield [2], UK

Objectives: The goal is to design a procedure that creates a patient
specific in silico model of the spine. This model shall evolve and adapt
depending on the real time action of the clinician during the clinical
procedure. At each surgical step, the in silico model will test several
scenarios and propose to the clinician the best placement of implants.
Each possible scenario of implants configuration and order of their
placement can be modelled by finite elements model. When the operation
is oriented on an individual patient and not on average spinal column,
the approach based on resolution of a complete model becomes too
computationally expensive, because multiple configurations have to be
tested in order to find the optimal one. As a consequence, this approach
cannot be efficiently introduced into medical practice. Recently, the AI
solutions have proven to be of great interest for medical applications.
The main goal of the future ESR will be the introduction of the reduced
order model based on machine learning techniques. Both the real medical
data and the results of the finite elements analysis will be used for
training of this model.

Required Skills: This ESR should have or be close to obtaining a minimum
undergraduate Honours degree (UK 2:1 or better) or MSc (Merit or
Distinction) in Engineering, Mathematics, Statistics, Signal Processing,
or a related discipline. Knowledge of modelling and simulation is
essential. Knowledge of deep learning, artificial intelligent and image
processing is desirable.

Acquired skills: The ESR will obtain very strong fundamentals on the
deep learning techniques and their applications in biomedical studies,
GPU computing.

Employability: The ESR will receive a strong background in deep learning
applied to biomechanics and therefore companies requiring modelling
expertise in the orthopaedic sector or in the biomedical engineering
field, or any other engineering field will be interested in such
profile.

Informal enquiries: Kateryna Bashtova (kateryna.bashtova at adagos.com) or
Lingzhong Guo (l.guo at sheffield.ac.uk).

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Links:
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[1] http://www.adagos.com/
[2] https://www.sheffield.ac.uk/