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PhD
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AS2M : 3Modeling, fabrication and control of dynamically tunable dry adhesion system for robotic micromanipulation"

Context and objective : Precision manipulation and assembly of micro-objects is one of the most challenging steps in micromanufacturing. Indeed, the interaction between tweezers and a micro-object is highly disturbed by specific physical effects predominant in microscale such adhesion. The design of microgrippers requires to take into account these specificities during the design of both the structure of the gripper and its controller. Several ways have been explored in robotic micromanipulation and one of the remaining challenges is to find active principles to actively control the adhesion during the manipulation tasks.

Scientific content :The chosen approach in this project consists of developing new grippers able to control the adhesion forces between the gripper tips and the manipulated object by acting actively on the tips of the gripper. One of the essential elements in this project is the control of the adhesion force to break the contact between two objects, which is called the pull-off force. The first objective requires studying and modeling the interactions between the gripper fingers and micro-objects of various shapes and typical sizes between 1μm and 200μm.

Profile : We are looking for a highly motivated, creative, and ambitious student with a good command of English (written and spoken), who can work well in a team as well as independently and quickly acquire knowledge in new topics. The ideal candidate must fulfill ateleast 3 of the following requirements : • Successfully completed scientific university degree (Master, Diploma or equivalent)
in Robotics, Materials Science, Materials Engineering, Mechanical Engineering or
other closely-related discipline with outstanding results,
• Experience in material characterization, including optical and electron microscopy,
mechanical properties of materials,
• Excellent knowledge and experience in robotics and manipulation,
• Experience in additive manufacturing of materials,
• Familiar with Matlab, Python, C++, CAD softwares and Finite Element Methods
• Experience in composing academic writing pieces (manuscripts, reviews, etc.)
• Innovative and entrepreneurial mindset

Contact: 

Please send your Curriculum Vitae (CV), a covering letter including research statement and the last year marks to Wissem Haouas : wissem.haouas@femto-st.fr

+ d'infos :
PDF icon sujet_th_se_smartdigitbot.pdf

AS2M : "Contribution to diagnostics and prognostics of Hyperparathyroids based on expert knowledge and artificial intelligence data fusion"

Context : In general, there are different types of data available to plan a therapy. These data can be from blood tests, imaging, radiographic or nuclear images, electrocardiograms, etc. In this thesis, we deal with the diagnosis of parathyroid pathologies for which there is no automatic process of localization, visualization and detection of this diseases. Practitioners have to use Nuclear Imaging with the use of two X-ray tracers with different operations of 3D reconstruction then subtraction with highlighting of the parathyroids after a grey level shift. The treatment is still requiring manual adjustment of the parameters used, with the result depending on the operator before the images are interpreted. It is then necessary to use machine learning techniques to identify the right parameters, different for each acquisition to automate the process. Thus, thanks to the knowledge of the many known clinical cases (several hundred) at the Besancon University Hospital in the nuclear medicine department of the heart-lung unit, it will be possible to train a model derived from artificial intelligence (AI) to do this diagnostic assistance work, under the control of the department's practitioners. [...]

Supervision and research team : The PhD will be supervised by Moncef Soualhi (UFC Besancon), Jean-Marc Nicod (ENSMM Besançon), Noureddine Zerhouni (ENSMM Besançon), Laurent Comas (CHU Besançon) and Hatem Boulahdour (CHU Besançon). Thus, the supervision team is composed by automation and data scientist researchers in PHM field in multidisciplinary projects. Moreover, the thesis will be developed within hospital professor and informatic experts give significance to the image processing and artificial intelligence algorithms in this field.

Applicant Profile : The candidate with a Master's degree in computer science, data science, mathematical application, automation should have a broad knowledge of image processing, including deep learning techniques and their implementation in software and hardware. Fundamental notions in data explore are also required. Fluency in English is essential. Autonomy, scientific rigor and a strong motivation for the proposed subject will be undeniable assets to successfully complete the thesis. The programming langage can be with Matlab, Python, C++

Candidate to be sent on 23th May 2022

Contact: 

Applicants are invited to submit their application to the PhD supervisors.
Application must contain the following documents:
- CV
- Cover letter + Master Grades
- At least 1 reference letter and recommendation

nourredine.zerhouni@femto-st.frjm.nicod@femto-st.frr & moncef.soualhi@femto-st.fr

 

+ d'infos :
PDF icon thesis_phm_nucleaar_imaging.pdf

MN2S: PhD in Numerical Optimization of Electromagnetic Metasurfaces for Opto-Mechanical Microrobots Actuation

Description:

In this thesis, the work will focus only on optical trapping. To extend these possibilities, the project will invest in the use of optical and elastical metamaterials: these are artificially structured materials with novel electromagnetic properties combined with controlled swimming properties. This approach aims at engineering the light/matter interaction, and has an obvious impact on optical tweezers, for example to increase the force generated. Metasurfaces and special metallic structures were used to increase the light-matter interaction. Beyond what can be achieved by a classical continuum approach, only a few works have explored beyond this limit with materials with optical gain.

The work will be theoretical and will be performed using finite elements.

 

How to apply:

Please send your Full application in a single PDF (CV, Cover Letter, Master Grades and 2 Reference Letters)

Deadline: 24 May 2022

AS2M : PhD in Energy based modeling and control of a dielectric elastomer cardiac assit device

The thesis will be a joint work between the Automatique et Syst`emes Micro-M ́ecatroniques (AS2M) department of FEMTO-ST Institute in France and the Integrated Actuators laboratory (LAI) of EPFL in Switzerland.

Context : The research activities of AS2M department cover automatic control, nano- and micro-robotics, mechatronics, and artificial intelligence. The research group PHS (port-Hamiltonian systems) has a strong knowledge on energy-based modeling and control of multiphysics systems, with an application on soft actuators, biomedical robots, and fluid-solid interactions, etc. The LAI (Integrated Actuators Laboratory) of EPFL (Ecole Polytechniques F ́ed ́erale de Lausanne) is specialized in modeling and design optimization of piezoelectric motors and actuators. Since 2018, with the establishment of the CAM (Center for Artificial Muscles), the LAI has a particular research activity focusing on the design, fabrication and modeling of artificial muscles with the use of electroactive polymer actuators. Last April, the CAM team has successfully implemented a tubular dielectric elastomer actuator on the descending aorta in order to assist the cardiac function in a porcine model.

This thesis has three main activities:

  1.  Modeling: develop a reliable model of the tubular DEAs considering the multi-physical, nonlinear and distributed parameters properties. The distributed parameter model will be discretized with a structure-preserving way and simulated hereafter.
  2.  Control: design passivity-based control laws using the proposed distributed parameter model with the aim to solve the electro-mechanical instability of the actuators. Both the modeling and controller design work will be carried out in AS2M, FEMTO-ST.
  3. Experiment: an experimental set-up will be built in order to validate the proposed model and to test the proposed control design methods in LAI, EPFL.

Application : The candidate will have to demonstrate a strong motivation for scientific research and very good level of English language skills. He or she will have to demonstrate a great rigor in work, method, autonomy, and ease in modeling, analyzing, and experimenting. He or she will have to hold a Master/ Engineering degree in Automatic control, Mechanical engineering, Microengineering, Mechatronics or Robotics. The candidate must be proficient in Matlab & Simulink simulation and have excellent programming skills. A knowledge of dynamic mathematical models and model analysis under the port-Hamiltonian framework and/or a first experience in using Labviex would be a plus.
List of documents to be provided:
• A CV.
• A motivation letter.
• An academic transcript and ranking of Master 1 and 2.
• Recommendation letters.

Deadline : 15 juin 2022

MN2S : PhD on Nucleate boiling: heat transfer mapping and study of mechanisms at wall-fluid interfaces

Context : This thesis is part of the TraThI project (Thermal Transfer at Interfaces) labelled by the ANR in 2021. It aims to study heat transfer at the transition between convective and nucleated boiling regimes, at micro
and macro scales. This ANR is a partnership between the institutes IUSTI, FEMTO -ST and IMFT (in France) and LTT-UL (Slovenia). The objective of the project is to understand in detail the mechanisms at the wall-fluid interfaces in order to develop new strategies to improve the heat transfer between a fluid and a wall. The project anticipates the challenges to be met in the fields of energy technologies and industry of the future, where the flow densities are an order of magnitude higher than those
accessible by current techniques.

Research unit : thesis co-directed by the University of Bourgogne Franche-Comté and the University of Aix-Marseille:
• FEMTO-ST institute, 15 B avenue des Montboucons, 25030 BESANCON cedex (University of Bourgogne Franche-Comté), FRANCE
• IUSTI laboratory, 5 rue Enrico Fermi, 13453 MARSEILLE Cedex 13 (Universit y of Aix-Marseille), FRANCE

Background :
− Master II or Engineer level

Application deadline : 30/04/2022

OPTICS : Photonics PhD EIHPI THEIA

We are pleased to open a Ph.D. position in photonics at CNRS and FEMTO-ST institute. The challenge is to provide new photonic building blocks for AI, biomedical diagnosis, or free space telecommunication systems. Multi-scale LiNbO3 photonic systems are at the heart of the project, and the objectives are to develop multi-channel photonic waveguides and interconnects.
The project lifts the barriers of ultra-dense photonic integration with the advent of active circuits implementing more than 100 channels per μm2.

By proposing new generic integration technologies based on the resources of the MIMENTO technology center, the thesis paves the way towards ultra-dense 3D photonic systems while also addressing crucial challenges in free-space optical telecommunications and biomedical diagnosis.
Three industrial partners are committed to the project.

Tasks:
- Technological developments of LiNbO3 nanoguides and
multichannel waveguides
- Modelization and testing
- On-site characterization

Candidate Profile : We are looking for applicants with a strong academic background who have completed a five-year master degree (3+2) within Physics, or Photonics preferably acquired recently