Theses available

  • 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

  • The NICHOID scaffold potentiates stem cells pluripotency and therapeutic efficacy

This thesis will be conducted at the Pediatric Clinical Research Center “Romeo and Enrica Invernizzi”, L. Sacco Department of Biomedical and Clinical Science, Università degli Studi di Milano. The work consists in the validation of a specific 3D engineered scaffold that mimics the native stem cell niche.

The potential findings of this project will allow the development of more efficient stem cells therapies for clinical translation. The technological part consists in the optimization and micro-fabrication of the scaffolds, suitable for stem cells of different origin. The consequent biological validation is focused on both in vitro and in vivo approaches.  AIM1: the candidate will investigate the stemness, differentiation capabilities and the gene expression profile with bioinformatic approaches. AIM2: the candidate will investigate the therapeutic efficacy and safety of cells expanded in the newly developed 3D niche in a preclinical animal model of Spinal Cord Injury.

Tutors: Dr. Stephana Carelli (stephana.carelli@unimi.it), Ing. Bianca Barzaghini (bianca.barzaghini@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

  • In silico and in vitro validation of a miniaturized multi-organ bioreactor

The thesis is based at the Department of Molecular Medicine at University of Pavia (Università di Pavia) and at the Departments of Chemistry (Politecnico di Milano – Campus Leonardo).
From April 1st and requires 1 year.

The work is both computational and experimental.

Computational part (@ Politecnico & home):

It consists in CAD design of a miniaturized milli-fluidic multi-organ perfusable bioreactor and the computational analysis, characterization and prediction of all the fluid dynamics and mass transport phaenomena. The candidate will use 3D modelling software (e.g. Solidworks, Inventor etc.), and Comsol Multiphysics.

Experimental part (@Università di Pavia):

The candidate will take part to the experimental campaign to validate the system. The lab work will include cell manipulation, scaffold fabrication and system set up. Finally, he will perform analyses using live imaging techniques and biochemical essays.

The ideal candidate should be familiar with computational tools and a have a strong attitude in problem solving.

Tutors: Ing. Alberto Bocconi (alberto.bocconi@polimi.it), Prof. Manuela T. Raimondi (PoliMI), Prof. Alessandra Balduini (UniPV)