Theses available

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

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

In order to evaluate the role of mechanotransduction in tumor progression, the project aim is to study 3D cultured human breast cancer cells by using both confocal Raman imaging – providing detailed biochemical mapping of cells – and Brillouin microscopy –able to investigate viscoelastic properties of cells in a non-destructive and contact-free approach, at the same time. The candidate will first optimize the bimodal Raman-Brillouin microscope, then he/she will use it to extract highly informative data.

The project includes a collaboration with a company focused on Brillouin microscopy (Specto photonics).

The ideal candidate should have a good knowledge of object-oriented coding languages (Python [preferentially] or MATLAB) and interest in both optics/photonics and applied biology.

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

  • 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

  • Identification of repurposable drugs and drug combinations in the panorama of synthetic lethality cancer therapy for metastasis prevention.

 The thesis is based at the Mechanobiology Lab of Politecnico di Milano (Dipartimento di Chimica, Materiali e Ingegneria Chimica “Giulio Natta” – Ed. 6) and will be half computational and half experimental.

The aim of the work is to perform a drug repurposing operation exploiting the concept of synthetic lethality, investigating in particular those couples involved in metastasis formation. The candidate will be asked to carry out a first fundamental part of exploration, integration and analysis of several types of data from different databases. Then, he/she will perform drug/drug combination testing on cells cultured in an innovative 3D environment. 

The ideal candidate should have a good prior knowledge of at least one programming language (R or Python).

Tutors: Ing. Carolina Testa (carolina.testa@polimi.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 design of 3D models and their 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 scaffold 3D bioprinting process optimization.

The candidate will use 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