IFOM

Bioinformatics Data Analyst

2025/04 | Milan

 

Are you interested in the Dark Proteome and Alternative Splicing?

We are excited to invite applications for a Bioinformatics Data Analyst to join the Molecular Machines in Signalling Pathways group, led by Prof. Simona Polo at IFOM (Milan) - https://www.ifom.eu/en/cancer-research/researchers/simona-polo.php

This role offers a unique opportunity to work in a highly collaborative, multidisciplinary environment, bridging RNA biology, structural protein modeling, and cancer research through advanced computational tools and multiomics analysis. The successful candidate will play a central role in decoding how alternative splicing impacts protein structure and function in colorectal cancer, with the goal of identifying novel disease drivers and therapeutic targets.

Your Role

You will work closely with wet-lab researchers on projects connecting gene expression variation to functional protein alterations. Your responsibilities will include:

  • Analyzing bulk and single-cell RNA sequencing datasets from colorectal cancer cell lines and patient-derived organoids;
  • Identifying alternative splicing events and functionally relevant isoforms using tools such as DEXSeq, StringTie, and Cufflinks;
  • Developing, optimizing, and maintaining computational workflows to manage large-scale transcriptomic data;
  • Integrating transcriptomic data with protein structure prediction tools (e.g. AlphaFold3) to investigate splicing-driven conformational changes;
  • Assisting in RNA structural analysis using chemical probing data;

Who You Are

You are passionate about combining computational analysis with biologically meaningful questions, and you enjoy navigating between data, tools, and hypotheses. You bring:

  • A Master’s degree (or PhD) in Bioinformatics, Computational Biology, or a related field;
  • Proficiency in R and Python;
  • Strong experience in RNA-Seq analysis, including alignment, quantification, and splicing event detection;
  • Experience in large-scale multi-omics data analysis (e.g., ATAC-seq, RIP/ChIP-seq);
  • Familiarity with protein structure modeling tools such as AlphaFold, and databases like GTEx, MANE;
  • Strong analytical thinking and problem-solving capabilities;
  • Excellent communication and collaboration skills, with a team-oriented mindset;

Why Join Us

At IFOM, you'll be part of a dynamic and diverse scientific community, working closely with leaders in cancer research, as well as in molecular, cellular and computational biology. 

You will:

  • Access cutting-edge technologies;
  • Contribute to impactful, peer-reviewed publications;
  • Grow in a supportive, internationally recognized research institute;

How to Apply 

Send a single PDF to simona.polo@ifom.eu containing:

  • Your CV, highlighting relevant experience and skills;
  • A short cover letter explaining your interest and suitability for the role;
  • Contact details for two references;

 

last update: 18/04/25
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