Postdoc in Cancer Synthetic Lethality Prediction and AI-Driven Target Discovery (AI)

TL;DR

Postdoc in Cancer Synthetic Lethality Prediction and AI-Driven Target Discovery (AI): Predicting synthetic lethality in cancer through AI, multi-omics data integration, and functional genomics with an accent on representation learning, nonlinear embeddings, and predictive modelling of genetic interactions. Focus on designing next-generation genetic interaction screens for anti-cancer target discovery.

Location: Based in Milan, Italy

Salary: up to €43,000 depending on candidate seniority

Company

hirify.global is a rapidly expanding life science institute in Milan where international researchers use cutting-edge technologies to accelerate biomedical discovery in computational biology, functional genomics, and precision oncology.

What you will do

• Lead computational genomics research at the intersection of machine learning, CRISPR screening, and multi-omics to uncover genetic interactions and synthetic lethalities in cancer.
• Develop scalable, reproducible methods for analyzing large-scale perturbation and omics datasets, translating into experimental strategies with wet-lab teams.
• Drive scientific output through publications, conference presentations, grants, and open science resources.
• Provide leadership by mentoring juniors and co-leading projects aligned with funded initiatives.

Requirements

• Ph.D. in Computational Biology, Bioinformatics, Machine Learning, Systems Biology, Genomics, or related field (or final stages).
• Track record of peer-reviewed publications.
• Experience with large-scale genomics or functional genomics datasets.
• Strong programming in Python and/or R, with Git.
• Familiarity with ML frameworks (scikit-learn, PyTorch, TensorFlow) applied to biomedical data.

Nice to have

• Experience with CRISPR screening, RNA-seq, single-cell or spatial transcriptomics.
• Handling multi-omics and perturbation data with focus on reproducibility and interpretability.
• Collaboration with wet-lab for experiment design (e.g., CRISPR screens).
• Reproducible environments (Docker, Snakemake, Nextflow).
• Strong math/statistics background.

Culture & Benefits

• International, dynamic, interdisciplinary environment.
• Competitive welfare, flexible working policies, relocation support.
• Tax benefits for researchers moving to Italy.
• Work-life balance and parental support initiatives.
• Career development through training, mentoring, and learning opportunities.

Hiring process

• Submit CV, motivation letter (English), and contact details of two referees.
• 4-year contract under CCNL Chimico Farmaceutico, Employee Level B2.
• Application closing date: 01.05.2026.