Post-Doc Bioinfromatician

Job title  Post-Doc Bioinfromatician

Within the National Recovery and Resilience Plan (PNRR), the IRCCS Humanitas Research Hospital has started public selection processes for recruitment in the context of projects aimed at enhancing and strengthening biomedical research within the National Health Service (SSN).

Project: Early diagnosis of high-grade serous epithelial ovarian cancer through the analysis of DNA derived from Pap Test smear (rif interno KMN314 - CUP: E23C24000310006)

Early diagnosis of ovarian cancer through the analysis of Pap test DNA. Preliminary results from a recent study (Paracchini, Mannarino, et al. Science translational Medicine, 2023) have demonstrated the possibility to intercept genomic instability, a specific hallmark of ovarian cancer, in the DNA extracted from Pap test smears of women that would have developed cancer in the subsequent years. Through this approach it is possible to quantify the overall genomic instability by assessing the copy number profile abnormality (CPA). When the CPA is more than 0.61, it indicates the presence of tumor DNA. In order to increase the performance of this test in terms of sensitivity, specificity and accuracy, an improvement of the approach is needed. The underlying hypothesis is that not only genomic instability is a marker of the presence of the tumor, but that there are other molecular features such as DNA methylation that contribute to tumor detection. A multi-level omic approach and the clinical features of patients could be informative and can contribute in the improvement of the test.

Professional profile and brief description of the required activities:

Post-Doc (phd’s, post doc, tecnico, data analyst, medico, data manager, ecc)

Activities:

The candidate will manage sequencing data from different sources (genomic, epigenomic) and will integrate them with other data types, such as clinicopathological features of recruited cases, using machine learning approaches. The aim is to develop, test, improve, and finalize a machine learning algorithm which allows the classification of the likelihood of ovarian cancer occurrence.

Required qualifications:

• Master’s degree in bioinformatics/engineering/physics/mathematics/biotechnology or equivalent.
• PhD in biomedical sciences/life science/biotechnology or equivalent.

Technical skills:

• Good knowledge of Python, R, Bash. Knowledge of Git and containers (Docker, Singularity);
• Good knowledge of workflow languages (nextflow);
• Knowledge of high-performance computing (HPC) systems;
• Good knowledge of machine learning approaches.

Preferred requirements:

• At least 3 years of experience in the application of bioinformatics to experimental research;
• Documented experience in collaborating on open-source projects.
• Knowledge of written and spoken English (B2)
• Excellent communication skills
• Ability to work in a team.

On the basis of the profiles received and in the terms indicated by this notice, Humanitas will activate the selection process by inviting suitable candidates to participate in selection interviews, after verification of the cv and qualifications, which will be held in presence or in telematic mode.

The selection committee, composed of the Project Manager and the Human Resources Department, will take charge of the overall evaluation of the applications received

Open Position (published): 10/09/2024

End Published: 10/10/2024

The notice is addressed to candidates in compliance with Dlgs 198/2006 and Dlgs 215/2003 and 216/2003. Interested persons are invited to read the privacy notice ex art. 13 and 14 of EU Reg. 2016/679.