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6th Call for Projects: 6 projects funded in 2023
On The May 15, 2023
2 PhD theses, 3 post-doctoral fellowships and 1 master internship are funded by the Graduate School after the 6th Call for Projects.
- ULTRACHEM (Axis #1)
Ultrafast laser interaction for chemical and topological functionalization of surfaces
PhD thesis funded on a research project led by Florence Garrelie (LabHC), a collaboration between the Hubert Curien lab (LabHC), the Georges Friedel lab (LGF), the Manutech-USD technical platform and the NEXQT Institute (formerly CRPUO, Ottawa, Canada).
- NANOTRAP (Axis #3)
TRAPping of extracellular vesicle by femtosecond laser-generated NANOstructures: a new approach to surface biofunctionalization
PhD thesis funded on a research project led by Virginie Dumas (LTDS), in collaboration with the SAINBIOSE lab and the Hubert Curien lab.
- PIMALEA (Axis #2)
Physics-Informed MAchine LEArning: From Extraction to Transfer of Knowledge in Surface Engineering
Eduardo Brandao, post-doctoral fellow, will work with Rémi Emonet (LabHC), in collaboration with Jean-Philippe Colombier (LabHC).
- QUMIN (Axis #2)
Quantitative in situ imaging and machine learning of cell/matrix mechanical interactions for cell biology
Cholé Techens, post-doctoral fellow, will work at the SAINBIOSE lab under the supervision of Stéphane Avril and in partnership with the Georges Friedel lab (LGF), the Hubert Curien lab (LabHC), the DCAC lab and Yale University (CT, USA).
- VEZPA (Axis #3)
VErsatile ZnO-based Plasmonics semiconducting substrates for biomedical Applications
Promod Kumar will work with the project leader François Goutaland, in partnership with Georges Friedel lab (LGF) and the Physics Department of the University of the Free State (Bloemfontein, South Africa)
- MONBONE-2 (Axis #3)
SPR-based biosensors for in vitro bone models
The recruited master student will work under the supervision of Donata Iandolo at the SAINBIOSE lab.
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SPR-based biosensors for in vitro bone models
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TRAPping of extracellular vesicle by femtosecond laser-generated NANOstructures: a new approach to surface biofunctionalization
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Physics-Informed MAchine LEArning: From Extraction to Transfer of Knowledge in Surface Engineering
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Prediction of laser-printed multidimensional colours on plasmonic metamaterials using deep learning and adaptative strategies
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Quantitative in situ imaging and machine learning of cell/matrix mechanical interactions for cell biology
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Ultrafast laser interaction for chemical and topological functionalization of surfaces
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VErsatile ZnO-based Plasmonics semiconducting substrates for biomedical Applications
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