Postdoc in Predictive Models for Anti-Cancer Therapeutic Target Prioritisation

Job description

APPLICATION CLOSING DATE: February 25th, 2024

About Human Technopole (HT)

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 currently composed of five research centres: Computational Biology, Structural Biology, Genomics, Neurogenomics, and Health Data Science. The Centres work together to enable interdisciplinary research and to create an open, collaborative environment that will help promote life science research both nationally and internationally.

About the Iorio Lab

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.

Our lab has recently been awarded an ERC Consolidator Grant (grant n.101125051), funding the DepSHOCK project. The project focuses on identifying robust transcriptional markers of cancer cell vulnerabilities. These markers will be used together with single-cell transcriptomic profiling of cancer models, to advance personalised medicine and the rational design of anti-cancer combinatorial therapies.

Leveraging prior knowledge from the Cancer Dependency Map , this project will generate post-perturbational transcriptomic datasets at both bulk and single-cell resolution, upon individual CRISPR-based genetic knockouts of relevant cancer dependency genes in associated dependent cancer in vitro models, as well as in a pooled fashion, using scale-limited libraries of single-guide RNAs.

About the position

We are actively seeking a Postdoc to play a key role in the DepSHOCK project. The selected candidate will be an integral part of the research lab and project team closely interacting with the data generation staff and they will be responsible for advanced computational tasks throughout the DepSHOCK work packages. They will extend existing algorithms and tools or design and implement novel analytical methods to support data analysis, curation, interpretation, and exploitation for precision anti-cancer target discovery and personalized medicine.

The chosen candidate will work on the DepSHOCK project alongside a lab technician and another postdoc, other members of the Iorio Lab, and the HT Computational Biology Research Centre, including computational scientists and bioinformaticians, for the analysis of generated data.

The successful candidate will report directly to the Group Leader, Dr. Francesco Iorio.

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. The HT Data Centre provides a state-of-the-art High-Performance Computing infrastructure and Data Storage support to meet all the computational needs of HT’s research groups.

Key Tasks and Responsibilities:

• Mining existing cancer dependency map datasets to prioritise cancer dependency genes and corresponding dependent cancer cell lines for inclusion in the DepSHOCK project.
• Computational deconvolution of longitudinal bulk-RNA/proteomic profiles of cancer cell lines upon individual gene knockouts (DepSHOCK footprints).
• Investigating the predictive ability of the DepSHOCK footprints using existing pattern-matching strategies and novel machine intelligence methods.
• Analysis and deconvolution of data from scaled-limited CRISPRscreens with single-cell transcriptomics readouts.
• Designing and using methods to exploit the DepSHOCK data for therapeutic marker discovery and for the design of combinatorial therapies.
• Generating novel scientific hypotheses, interpreting results, writing scientific manuscripts, and disseminating findings through participation in conferences and scientific meetings.

Job requirements

Key Tasks and Responsibilities:

• Mining existing cancer dependency map datasets to prioritise cancer dependency genes and corresponding dependent cancer cell lines for inclusion in the DepSHOCK project.
• Computational deconvolution of longitudinal bulk-RNA/proteomic profiles of cancer cell lines upon individual gene knockouts (DepSHOCK footprints).
• Investigating the predictive ability of the DepSHOCK footprints using existing pattern-matching strategies and novel machine intelligence methods.
• Analysis and deconvolution of data from scaled-limited CRISPRscreens with single-cell transcriptomics readouts.
• Designing and using methods to exploit the DepSHOCK data for therapeutic marker discovery and for the design of combinatorial therapies.
• Generating novel scientific hypotheses, interpreting results, writing scientific manuscripts, and disseminating findings through participation in conferences and scientific meetings.

Essential requirements

• A PhD degree (obtained within 6 months after the call closure) in a relevant subject, e.g., bioinformatics, computer science, mathematics, physics, engineering, or a related field of science.
• Hands-on experience in data science, preferably in life sciences or medicine.
• 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.
• Familiarity with cancer genomics.
• Proven track record demonstrating the ability to lead projects independently.
• Experience with the analysis of data from single-cell CRISPR screens, 10x single-cell assays and native computational tools.
• Familiarity with the Cancer Dependency Map and portfolio of tools and resources is considered advantageous.

Organizational and social skills:

• Ability to manage competing priorities in a fast-paced environment and to work independently.
• Proven leadership experience, with strong organization, communication, team-building, and problem-solving skills.
• Strong interpersonal skills demonstrated by the ability to lead and gain the assistance and cooperation of others in a team endeavour.
• Ability to work in a multi-cultural environment with sensitivity and respect for diversity.

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, [email protected] (this email address should not be used to send applications).

Why Human Technopole

HT seeks scientific excellence, we recruit the best scientific talents through international, open calls.

Our working environment is international, friendly and inclusive. Our scientists work together across disciplines on research topics of biomedical relevance, leveraging synergies between their diverse skillsets and methodological approaches.

We believe that highly diverse teams yield the best and most innovative results.

We engage in outward-facing scientific activities aimed at benefiting the national and international research community. Training is also at the heart of our activity, with initiatives and opportunities for our staff, including scientific courses, conferences and workshops.

Main benefits

• Welfare plans.
• Canteen service.
• Work-life balance provisions.
• Italian language training for foreigners.
• Maternity leave up to 1 year and other support for new parents.
• Counseling.
• Possibility of flexible working hours
• Support for relocation.
• Tax benefits where applicable.

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 5 years - employee level.

The position is based in Milan.