XenOmics – An Innovative Risk Assessment Toolkit Based on Omics Methodologies and Artificial Intelligence for Occupational Safety

id="offer-description" class="ecl-u-type-heading-2 ecl-u-mt-none ecl-u-mb-l">Offer Description The research aims to study Machine Learning (ML) strategies for the integration of omics and environmental data, the identification of potential biomarkers, and the development of a predictive model for toxicological risk. Where to apply Website https://dsb.uniroma1.it/ . Requirements. Additional Information . Eligibility criteria. - Final degree grade (up to 10 points). - Publications: up to 5 points. - Other qualifications related to the activity performed, such as research/work contracts, scholarships or fellowships, and official assignments: up to 25 points. - Interview: up to 40 points. Eligible destination country/ies for fellows: . Italy. Eligibility of fellows: country/ies of residence: . EUROPE. Eligibility of fellows: nationality/ies: . EUROPE. Selection process. The interview will center on verifying the candidate's competencies in statistical data analysis and machine learning, alongside scientific programming in Python. Website for additional job details https://trasparenza.uniroma1.it/page/5/details/36960/bando-per-il-conferimento-…. <h2