Nonlinear Spectroscopy and Microscopy for Biomedical applications
Development of new methods for optical non-linear microscopy to be applied to biophysics and medical physics in-vivo. In this field the Biophotonics group is developing two-photon excitation fluorescence imaging microscopy and second harmonic generation microscopy. One of the main application aims to the study of the motion of lymphocytes in lymph nodes in order to model the immune response of mice. This work is being carried out in collaboration with the Biotechnology group of our University.
Adaptive optics for imaging through tissues in-vivo
The formation of images through opaque media has applications ranging from engineering to electronics and medicine and biotechnology. The wave front of light is strongly modified by the inhomogeneities of the medium in which it propagates over a wide range of spatial frequencies. In order to correct these effects, various programmable reflective or diffractive elements such as deformable mirrors or spatial light modulators can be used. The purpose of the proposed theses is to couple these technologies, partly borrowed from observational astronomy, to optical microscopy techniques for the study of tissues both in vitro and in vivo.
Pozzi et al. J. of Biomedical Optics, 19(6), 067007 (2014) https://doi.org/10.1117/1.JBO.19.6.067007
Laser micro-fabrication of hydrogels for biomedical applications
Photo- polymerization can be used to fabricate hydrogels for cell culturing and tissue engineering. In particular we develop protein based photo-resists to fabricate, by means of lasers or UV LEDs, microstructures with high axial ratio (3 to 5) and small size (from 30 μm to 50 μm). We employ both UV sources (385 nm) or near infrared pulsed (femtosecond pulse width) lasers to obtain high resolution writing. The laser is scanned on the resist to induce polymerization or a mask is used in front of the UV LED. These methods are used to fabricate microstructures that can host cells for cell culturing or be implanted in vivo for tissue engineering.
Artificial Intelligence for digital pathology or Enviromental science
The physics of complex systems, from biophysics to Environmental Physics, requires the analysis of a considerable amount of data that depend on numerous parameters. There are therefore numerous areas in which Machine Learning and Artificial Intelligence methods can be used advantageously to organize the data obtained and to try to formulate chemical-physical models. In addition to this, the attempt to numerically simulate complex systems, such as the immune system, must go through the use of active learning methods. The theses offered in this area range from the development of correction systems for images taken in the optical range (UV-NIR) both in tissue microscopy and in environmental monitoring and X-ray or PET images, to the development of active learning methods for the analysis of numerical simulations of the immune system.
Characterisation of the role of prometastatic MICAL2 on nuclear envelope and genome integrity through transcriptional control of Lamin A/C
12 months post-doc position on the project.
Background. Over 90% of cancer deaths are due to metastasis, but the efficacy of adjuvant therapy in reducing metastasis provide just a few months of survival advantage. To increase our therapeutic arsenal for a more effective metastasis prevention or treatment, we need new targets. Preliminary data suggest a positive interplay between the promoters of MICAL2, of LMNA and of other proteins of the nuclear envelope (NE). However, we need extensive validation of the results.
Aim. The aim is to 1) correlate the expression of MICAL2 and LMNA in determining NE composition and mechano- transduction in cancer cells; 2) correlate spatial genome organisation and epigenetic regulation in function of MICAL2 expression;3) develop in vitro platforms for these studies that avoid the use of lab animals.
- development of 2D and quasi 3D platforms for cell culturing with varying rigidity
- confocal and non-linear excitation imaging on cells and study of the effect to the rigidity on their growth.
- PhD in physics, engineering, biotechnology, or related fields.
- Experience in laser optics, preferably optical scanning microscopy.
The position will start ideally around January 2024, pending official project start approval. The contract is a Gross salary 24000 Euro/year. The position is initially for one year with the possibility of an extension of 1 year.
Contacts. Giuseppe Chirico, Giuseppe.firstname.lastname@example.org
Funded by Progetto PRIN – Ministero dell’Università e Ricerca 2022. Collaborative project of Scuola Superiore Sant’Anna, Politecnico di Milano, and Università di Milano-Bicocca.
Post – doctoral position in image reconstruction
“Multiple Emission Tomography” Project
The multiple emission tomography (MET) project is a cutting-edge research initiative funded by the ministry of university and research. The aim of the project is to design and build a novel device for medical imaging that can operate as both a positron emission tomography (PET) scanner and a single photon emission tomograph (SPECT) when using a “Compton camera” mode. This innovative feature allows the device to reconstruct inter-crystal scattering events in the detector, which can enhance the image quality and resolution. Without the need for a collimator, sensitivity can be increased by a factor greater than 100.
Therefore, the MET project has the potential to revolutionize the field of theranostics, especially for applications involving high gamma energy isotopes (e.g.: > 250 keV) or positron emitting isotopes that emit a coincident third gamma.
The project is a collaborative effort between the university of Milano-Bicocca and the Torino unit of the national institute of nuclear physics (INFN). The principal investigator is Luca Presotto, from Unimib. The Torino unit is responsible for developing the electronics readout system, while Unimib is in charge of creating the crystals assembly, simulating the device performance, and developing image reconstruction algorithms.
The integration of simulations and image reconstruction algorithms will enable the evaluation of the expected final performance of the hardware, as well as the exploration of its clinical usefulness.
The candidate will be involved in the development of image reconstruction algorithms for the MET device.
The main tasks of the candidate will be to:
- Develop simulations of the MET hardware
- Adapt Compton camera image reconstruction algorithms to the specifics of the MET device: very high sensitivity but very low resolution, both that need to be incorporated into the reconstruction.
- Estimate the optimal spatial resolution that can be theoretically achievable, by the device as a function of the detector design
The candidate will work closely with the PI and other researchers from Unimib and INFN, and will contribute to the scientific publications and presentations of the project results.
The ideal candidate should have the following qualifications and skills:
- PhD in physics, engineering, computer science, or related fields.
- Experience in image reconstruction algorithms, preferably tomographic ones
- Proficiency in programming languages such as Python or Matlab, and familiarity with software development tools and practices.
Desirable but not essential:
- Experience in GPU coding and/or in GATE/GEANT software for Monte Carlo simulations
The position will start ideally around January 2024, pending official project start approval. The contract is a 2 year “assegno di ricerca” position with 30k€/year industry cost (approx. 1700€/month after taxes).