Postdoc in CRISPR Meta-Analytics and AI for Therapeutic Target Discovery and Priotisation (OT Grant)

APPLICATION CLOSING DATE: 14/06/2024
Human Technopole (HT) is a new interdisciplinary life science research institute created and supported by the Italian government, aimed at developing innovative solutions.

Situated in the Computational Biology Research Centre of HT, the Iorio Lab  operates at the intersection of biology, machine learning, statistics, and information theory. Our goal is to comprehend and predict how genomic alterations and molecular traits, derived from various omics, contribute to pathological processes, rewire biological circuits, and influence therapeutic responses in human cancers and other diseases.

Together with researchers at EMBL – European Bioinformatics Institute  and Wellcome Sanger Institute , our lab has recently been awarded an Open Targets  Research Grant funding the OT Perturbation Catalogue project (grant n.OTAR3089).

The project focuses on the creation of an online repository of data from functional genetics screens and, more generally, post-perturbational experiments (typically CRISPR screens with viability or transcriptomics readouts). We will focus on a specific meta-analytics work package of the OT Perturbation Catalogue project, developing computational methods for the reproducibility assessment 1 , harmonisation 2  and analysis of inter-study CRISPR datasets, aggregating data and developing and using innovative AI based-methods for therapeutic target prioritisation pipelines 3  on the resulting aggregated data for cancer 4 , neurodegenerative disorders and other diseases.

We are actively seeking a post-doctoral fellow to play a key role in the OT Perturbation Catalogue Project. The selected candidate will be an integral part of the team closely interacting with the other participating groups and the Open Targets consortium. They will extend existing algorithms and tools, and design and implement novel methods to support data analysis, curation, interpretation, and exploitation for target discovery and prioritisation.

The chosen candidate will work alongside other members of the Iorio Lab, and the HT Computational Biology Research Centre, including computational scientists and bioinformaticians.

HT benefits from accessibility to the HT National Facility for Genomics, providing state-of-the-art and innovative services ranging from high-throughput sequencing to multi-omics technologies.

Key Tasks and Responsibilities:

• Gathering existing cancer functional genomics and dependency map datasets, which are periodically revamped, in combination with the data already deposited in the OT Perturbation Catalogue, implementing methods for their comparisons and integration;
• Using existing computational pipelines and designing novel methods for computational meta-analysis of CRISPR datasets; for the aggregation and harmonisation of multiple inter-study CRISPR screens;
• Refining existing anti-cancer therapeutic target prioritisation pipelines and designing novel ones incorporating AI-based methods, then executing them on harmonised cancer-related perturbation data;
• Investigating how the developed methods could be extended to neurodegeneration and other diseases of interest, beyond cancer.
• Interacting with the other teams involved in the project across participating institutes, periodically presenting advances and results to Open Targets meetings and Integration days.

Job requirements

Essential requirements

• Hands-on experience in data science, preferably life sciences or medicine.
• A PhD degree (obtained at the call closure time or near completion) in a relevant subject, e.g., bioinformatics, computer science, mathematics, physics, engineering or a related field of science.
• Proven track record demonstrating the ability to lead projects independently.
• Experience in the analysis of genomics or functional-genomics datasets.
• Fluency in English – HT is an international research institute.

Preferred requirements

• Experience with the analysis of data from CRISPR-Cas9 screens, siRNA, shRNA, antisense oligonucleotides (ASOs) or similar technologies
• Experience with handling large-scale datasets.
• Statistics and Machine-learning background
• Familiarity with cancer genomics
• Familiarity with the Cancer Dependency Map and portfolio of tools and resources

Organizational and social skills

• Ability to interact effectively with other teams and work synergistically to drive projects forward.
• Proven communication, team building and problem-solving skills.

Application Instructions

Please apply online by sending:

i) a CV

ii) a motivation letter in English

iii) names and contacts of 2 referees

For any inquiry about the call, please feel free to contact Dr Francesco Iorio, Francesco.iorio [at] fht.org (this email address should not be used to send applications).

Additional Information

The remuneration package is internationally competitive and comprises a highly competitive salary, pension scheme, medical and other social benefits and support for relocation and installation. The contract is for 3 years with the possibility of a 2-year extension.

HT offers a highly collaborative, international culture to foster top quality, interdisciplinary research by promoting a vibrant environment consisting of independent research groups with access to outstanding graduate students, postdoctoral fellows and core facilities.

HT is an inclusive employer that fosters diversity and engages systematically to ensure that equal employment opportunities are provided without regard to age, race, creed, religion, sex, disability, medical condition, sexual orientation, gender identity or expression, national or ethnic origin or any other legally recognized status entitled to protection under applicable laws. HT offers attractive conditions and benefits appropriate to a leading, internationally competitive, research organisation that promotes a collegial and open atmosphere.

The Human Technopole Foundation is based in Milan, recently named the city with the best quality of life in Italy (https://lab24.ilsole24ore.com/qualita-della-vita/ ).

Main benefits

• Welfare plans.
• Canteen service.
• Work-life balance provisions.
• Italian language training for foreigners.
• Parental leave up to 1 year and other support for new parents.
• Counseling.
• Flexible working hours.
• Remote working policy.
• 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.

Contract offered: CCNL Chimico Farmaceutico, fixed-term 3 years - employee level.

The position is based in Milan.
Salary range: up to 40K.

Tax benefits where applicable.

“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”.

References

1. Dempster, J., Behan, F.M., Green, T., Najgebauer, H., Krill-Burger, J., Allen, F., and Others (2019). Agreement between two large pan-cancer genome-scale CRISPR knock-out datasets. Nat. Commun. 10, 5817.

2. Pacini, C., Dempster, J.M., Boyle, I., Gonçalves, E., Najgebauer, H., Karakoc, E., van der Meer, D., Barthorpe, A., Lightfoot, H., Jaaks, P., et al. (2021). Integrated cross-study datasets of genetic dependencies in cancer. Nat. Commun. 12, 1661.

3. Behan, F.M., Iorio, F., Picco, G., Gonçalves, E., Beaver, C.M., Migliardi, G., Santos, R., Rao, Y., Sassi, F., Pinnelli, M., et al. (2019). Prioritization of cancer therapeutic targets using CRISPR-Cas9 screens. Nature 568, 511–516.

4. Pacini, C., Duncan, E., Gonçalves, E., Gilbert, J., Bhosle, S., Horswell, S., Karakoc, E., Lightfoot, H., Curry, E., Muyas, F., et al. (2024). A comprehensive clinically informed map of dependencies in cancer cells and framework for target prioritization. Cancer Cell. 10.1016/j.ccell.2023.12.016.