• Generation of micro-structured 3D millifluidic chips to model endothelial regeneration

This thesis is based at the Mechanobiology lab c/o the Dept. of Chemistry “G. Natta” and the IFN-CNR c/o the Dept. of Physics (Politecnico di Milano – Campus Leonardo). The work is experimental, and it consists in the use of a millifluidic bioreactor to model endothelial formation. We will analyze the cell adhesion and organization of fibroblast, endothelial cells, and mesenchymal stem cells undergoing mechanical and chemical stimuli (drugs) to monitor tissue (re)generation. Ideal candidates are those willing to develop knowledge in laser-related materials technology and fluorescence microscopy.

Tutors: Dr. Chiara Martinelli (chiara.martinelli@polimi.it), Dr. Alberto Bocconi (alberto.bocconi@polimi.it), Prof. Emanuela Jacchetti (emanuela.jacchetti@polimi.it)

• Modeling macrophage phenotype by mechanotrasduction

This thesis is based at the Mechanobiology lab c/o the Dept. of Chemistry “G. Natta” and the IFN-CNR c/o the Dept. of Physics (Politecnico di Milano – Campus Leonardo).

Scaffolds will be mainly fabricated using a micro stereolithography technique called “2-photon laser polymerization”. Cell cultures will be performed using monocyte-derived macrophages, and their polarization will be investigated as a function of different scaffold architectures. Protein expression and localization will be investigated using biochemical assay and high-resolution optical microscopy, such as confocal and FLIM microscopy. Software, like ImageJ and Matlab, will be used to extract informative data from acquired images. Ideal candidates are those willing to develop knowledge in laser-related materials technology and optical microscopy applied to biological systems.

Tutors: Prof. Chiara Martinelli (chiara.martinelli@polimi.it), Prof. Emanuela Jacchetti (emanuela.jacchetti@polimi.it)

• Biochemical and mechanical 3D mapping of cancer cells by label-free Brillouin-Raman microspectroscopy

The thesis is based at the Department of Chemistry and at the Department of Physics (Politecnico di Milano – Campus Leonardo). The work is experimental but also involves computational tasks.

To evaluate the role of mechanotransduction in tumor progression and the immune system, the project aim is to study 3D cultured human cancer cells and macrophages mainly using optical

microscopy. The techniques employed will be confocal microscope imaging (to investigate organization and localization of proteins), FLIM imaging (to investigate cell metabolism), Raman imaging (providing detailed biochemical mapping of cells), and Brillouin microscopy (to investigate viscoelastic properties of cells in a non-destructive and contact-free approach).

The candidate will create 3D scaffolds to stimulate cell mechanotransduction and will investigate cell behavior. He/she will optimize the bimodal Raman-Brillouin microscope, and then software like ImageJ and Matlab or programming languages (such as phyton) will be used to extract informative data from acquired images. The project includes a collaboration with a company focused on Brillouin microscopy (Specto photonics).

Tutors and Advisors: Dr. Renzo Vanna (renzo.vanna@cnr.it), Dr. Giuseppe Antonacci (giuseppe@spectophotonics.com), Prof. Dario Polli (dario.polli@polimi.it), Prof. Emanuela Jacchetti (emanuela.jacchetti@polimi.it)

• Implantable medical device design and artificial Intelligence image processing in Foreign Body Response analyses

The thesis is based at the Department of Biophysics (Università di Milano Bicocca – U1) and at the Departments of Chemistry (Politecnico di Milano – Campus Leonardo). The work is mainly computational.

It consists in CAD design of a miniaturized implantable device and its realization with fast

prototyping additive manufacturing techniques (SLA-DLP). The candidate will remotely analyze fluorescence intravital images from mammalian device implantation by coding and applying machine learning algorithms aimed to image restoration. The candidate will use 3D modelling software (e.g. Solidworks, Inventor etc.), MATLAB and Python environments. The ideal candidate should have a good knowledge of object-oriented coding languages (C++, Python, MATLAB), capability in 3D modelling and a strong attitude in problem solving.

Tutors: Ing. Claudio Conci (claudio.conci@polimi.it), Prof. Laura Sironi (laura.sironi@unimib.it), Prof. Manuela T. Raimondi

• Study of the geometry of a 3D bioprinted scaffold to optimize the interaction with a liquid phase

The thesis is based at the Department of Chemistry (Politecnico di Milano – Campus Leonardo).

The work is computational; it consists in the recontruction of 3D models starting from 2D

sources and their subsequent study and characterization through multiphysical analyses (mechanical and fluid-dynamic simulations). The aim of the project consists in computationally validating a tumor – immune system interaction model. The validation will provide useful data to support the analysis of biological events.

The candidate will use image computing platforms, 3D modelling software (e.g. Solidworks), and multiphysics simulation software (e.g. COMSOL). The ideal candidate should already have familiarity with at least one of these tools and a strong attitude in problem solving.

Tutors: Ing. Paolo Ritter (paolo.ritter@polimi.it), Ing. Claudio Conci (claudio.conci@polimi.it), Prof. Manuela T. Raimondi

• Development of segmentation algorithms for digital pathology and deep learning algorithms for image registration (1 or 2 students)

The thesis is based at the Department of Biophysics (Università di Milano Bicocca – U1). The work is computational;

The aim of this project is to exploit state of the art in deep learning algorithms or to  develop novel pipelines to segment and characterize different cells populations in histology sections. In addition, candidates have to exploit also state of the art tools or to develop novel algorithms to register images acquired by means of different light microscopy techniques (histology, two-photon microscopy, brightfield, FLIM, hyperspectral), characterized by different resolutions and signal properties.

The ideal candidate should have a good knowledge of object-oriented coding languages (C++, Python, MATLAB).

Tutors: Prof. Laura Sironi (laura.sironi@unimib.it), Ing. Claudio Conci (claudio.conci@polimi.it), Prof. Manuela T. Raimondi