Call for fellowship
The Bioinformatics group at the Dpt. of Science and Technology, University of Sannio, is looking for a young researcher with interest in machine learning and bioinformatic data analysis to collaborate on a two-years interdisciplinary project.
Project description
Within the PRIN 2022 framework (with activities spanning through 2024-2025), the project is titled “Drug repositioning for Retinitis Pigmentosa by an Artificial Intelligence application to single-cell transcriptomics”. In collaboration with renown field experts, it aims to identify novel treatments for Retinitis Pigmentosa (RP), a rare inherited retinal disease, using an innovative AI-based approach that will leverage original data produced within our collaboration. In particular, scRNA-seq gene expression profiles will be fed to an adversarial deep learning model along the lines of previously published methodologies by our lab (see 10.1016/j.stemcr.2021.03.028 and 10.1101/2023.08.21.554075). The top drugs predicted in silico will then be validated in RP mice, involving the analysis of post-treatment retinal transcriptomes.
Group description
Our group includes biologists, biotechnologists and computer scientists with several international collaborations. The main interest of the group is the application of innovative computational techniques, such as deep learning architectures for domain adaptation, to elucidate or predict pathological, physiological and pharmacological mechanisms by integrating heterogeneous -omics data types.
Candidate description
We are seeking a motivated post-graduate with proved scientific experience or postdoctoral fellow with a background in Computer Science to join our lab under a 1 to 2 years contract ("assegno di ricerca"). A Master Degree in Computer Science, Statistics, Bioinformatics or other relevant disciplines is mandatory. A PhD in Computer Science, Bioinformatics or other relevant disciplines will be preferred. Previous experience with machine learning and bioinformatic data analysis, particularly in the R or Python environment will also be considered. On-premise work is preferred, remote work will be considered.
Application
The PI will be happy to receive direct enquiries before setting up the formal hiring process.
Principal Investigator
Francesco Napolitano
DST, University of Sannio, Benevento, Italy.
francesco.napolitano@unisannio.it