Postdoc In Cancer Synthetic Lethality Prediction And Ai-Driven Target Discovery

APPLICATION CLOSING DATE:
October 12, 2025

Human Technopole (HT) is an interdisciplinary life science research institute, created and supported by the Italian Government, with the aim of developing innovative strategies to improve human health. HT is composed of five Centers:
Neurogenomics, Computational Biology, Structural Biology, Genomics, and Health Data Science. The Centers work together to enable interdisciplinary research and to create an open, collaborative environment that will help promote life science research both nationally and internationally.

The Iorio Lab at Human Technopole (Milan, Italy) is seeking a talented, highly motivated computational Postdoctoral Researcher to lead a new project at the intersection of artificial intelligence, multi-omics data integration, and functional genomics, aimed at predicting synthetic lethalities in cancer and guiding the design of next-generation genetic interaction screens for anti-cancer target discovery.

The successful candidate will take intellectual and technical leadership of this project, driving forward the development of innovative computational frameworks and working in close collaboration with experimental scientists. In particular, the postdoc will have the opportunity to co-design computationally informed, biology-driven experiments, including CRISPR and Perturb-seq, single-cell transcriptomics, and spatial-omics screens.

We are looking for a scientist who thrives at the intersection of computational biology, machine learning, cancer genomics, and CRISPR-data analysis, who is eager to shape high-impact, translational research from the ground up.

We especially value candidates with a strong academic mindset, driven by curiosity and intellectual rigour, passionate about generating impactful scientific knowledge, and committed to open science, critical thinking, and continuous learning.

Key tasks and responsibilities

• Design and lead original research projects at the intersection of computational biology, machine learning, and functional genomics, with a strong focus on identifying synthetic lethalities and genetic interactions in cancer.
• Develop, benchmark, and apply novel computational methods for integrative analysis of CRISPR screening data, multi-omic datasets (e.G., transcriptomics, methylation, proteomics), and perturbation-response signatures, with emphasis on reproducibility and scalability.
• Actively collaborate with wet-lab scientists to translate computational insights into experimental designs, including CRISPR-based genetic interaction screens, single-cell transcriptomics (e.G., Perturb-seq), and spatial omics assays.
• Maintain thorough, accurate, and well-organised documentation of research activities in both electronic lab notebooks and shared repositories, ensuring traceability of results and compliance with open science practices.
• Generate publication-quality figures, data visualisations, and written contributions for peer-reviewed scientific manuscripts, preprints, grant applications, and public dashboards.
• Publish research outcomes in high-impact journals and present results at internal seminars, international conferences, and workshops, contributing to the scientific visibility of the lab and Human Technopole.
• Mentor and supervise junior scientists (e.G., students, interns, research assistants) by providing guidance on experimental design, data analysis, coding best practices, and scientific writing.
• Contribute to and co-lead collaborative projects , interacting regularly with HT internal research groups (e.G., GEDI, Computational Biology Centre), as well as national and international academic and industry partners.
• Work closely with the PI and senior leadership to define project milestones, allocate resources, and ensure alignment with strategic goals of funded initiatives (e.G., ERC DepSHOCK, AIRC, HT DELBRUCK Flagship project).

Essential Job requirements

On the closing date for online applications, the candidate must fulfil all the following conditions:

• Hold a Ph.D. in a relevant field, such as Computational Biology, Bioinformatics, Machine Learning, Systems Biology, Genomics, or a related discipline.
• Demonstrate a solid research background, supported by a track record of peer-reviewed publications in reputable scientific journals.
• Proven experience with large-scale genomics or functional genomics datasets.
• Strong programming skills in Python and/or R, with experience in version control (e.G., Git) and working in reproducible research environments (e.G., Docker, Snakemake, Nextflow).
• Familiarity with machine learning frameworks (e.G., scikit-learn, PyTorch, TensorFlow) applied to biomedical data.

Preferred Job requirements

• Familiarity with CRISPR-Cas9 or CRISPRi/a screening data, RNA-seq, single-cell or spatial transcriptomics data processing
• Competence in acquiring, handling, and analysing large and complex datasets, including multi-omics and perturbation-response data, with a strong emphasis on data quality, reproducibility, and biological interpretability.
• Practical experience in collaborative, hybrid settings, including direct interaction with wet-lab scientists, technicians, and experimental facilities to co-design and support integrated, computationally guided experiments (e.G., CRISPR-based screens, single-cell or spatial transcriptomics).

Organisational and social skills

• Excellent written and verbal communication skills, with the ability to work effectively in a multidisciplinary and international team.
• A strong academic mindset, combining scientific curiosity, technical rigour, openness to feedback, and commitment to mentorship and collaboration.
• Strong problem-solving and organizational abilities.
• Teamwork and good communication skills.
• Strong scientific communication skills, including the ability to write and revise manuscripts for publication, prepare compelling visual materials, and present findings to diverse audiences—from internal collaborators to external stakeholders, funders, and the general public.

About the lab

The Iorio Lab at Human Technopole (Milan, Italy) is a dynamic and internationally recognised research group working at the intersection of computational biology, functional genomics, and precision oncology. Founded in 2020, the lab has rapidly evolved into a hybrid computational/experimental team, now entering its second and more ambitious phase of growth. Our research combines machine learning, large-scale CRISPR screening, and multi-omics to uncover cancer vulnerabilities and drive therapeutic target discovery. Backed by major grants (including an ERC Consolidator Grant and an AIRC investigator grant) we contribute to initiatives like the European Cancer Dependency Map and collaborate widely across academia and industry.

We offer a vibrant, inclusive environment where postdocs lead high-impact projects and help shape the next generation of data-driven cancer research.

Application Instructions

Please apply online by submitting a single document that includes:

• a CV.
• a motivation letter in English (max 1 page long).
• names and contacts of at least 2 referees.

Main benefits

• Welfare plans.
• Meal delivery service.
• Work-life balance provisions.
• Italian language training for foreigners.
• Parental leave up to 1 year and other support for new parents.
• Flexible working hours.
• Support for relocation.
• Researchers coming to Italy for the first time, or returning after residing abroad, benefit from very attractive income tax benefits.

Special consideration will be given to candidates who are part of the protected categories list, according to L. 68/99.

Number of positions offered:
1

Contract offered:
CCNL Chimico Farmaceutico, Fixed-term 4 years - Employee Level

Tax benefits where applicable.

The position is based in Milan.

“The Foundation reserves the right, at its sole discretion, to extend, suspend, modify, revoke, or cancel this job posting without giving rise to any rights or claims whatsoever in favor of the candidates;
the Foundation reserves, however, the right not to proceed with the awarding of the above-described assignment due to the effect of supervening regulatory provisions and/or obstructive circumstances”.