Bioinformatics data analyst

We are excited to announce an opening for a Bioinformatics data analyst to join the research teams of the Casola and Tripodo Labs at IFOM, the AIRC Institute of Molecular Oncology. This position offers the opportunity to contribute to cutting-edge research in cancer immunology through an integrated analysis of gene expression, genomics, and spatial omics approaches. You will play a pivotal role in analyzing and interpreting high-throughput datasets, including bulk and single cell RNA sequencing, immunoglobulin/TCR genetics and spatial omics data, obtained from pre-clinical and clinical samples. The candidate will be integrated into a joined research effort led by the Casola and Tripodo laboratories aiming to dissect tumor-intrinsic and microenvironment-associated drivers of hematological cancers. The position is destined to a highly ambitious candidate interested to solve immunology-centred fundamental and clinically-oriented questions, using multi-disciplinary approaches, including artificial intelligence tools applied to pathology images and genetics data. By working within this collaborative and multidisciplinary environment, you will help drive innovative research projects that advance our understanding on how players of the adaptive and innate immune system become themeselves target of malignant transformation, confer anti-tumor immunity or support cancer progression. Identification of novel molecular, cellular or spatial biomarkers predictive of cancer evolution and therapy response represents one of the main goals the Tripodo and Casola laboratories aim to reach in the next five years. The candidate will play a key role in achieving this objective. Key Responsibilities Analyze bulk RNA sequencing and single-cell RNA sequencing datasets, deriving meaningful biological insights; Deconvolute antigen receptor repertoires from next-generation DNA/RNA sequencing datasets, including spatial transcriptoimics; Conduct in-depth spatial omics analyses using platforms such as Visium and CosMx; Develop, optimize, and maintain computational workflows to handle large-scale genomic and transcriptomic data; Work in close contact with wet bioloigists in the Tripodo and Casola labs to design and refine studies and interpret bioinformatics results, addressing key biological questions; Provide expert input on bioinformatics methods for grant applications and publications; Systematically document workflows and findings, sharing results with internal teams and external scientific audiences; What we're Looking For The ideal candidate will have a strong academic background, holding a Ph.D. or M.Sc. in bioinformatics, computational biology, or a related field. Proficiency in R and Python, with demonstrated experience in omics data analysis, is essential. Familiarity with bioinformatics tools for bulk RNA-seq, single-cell RNA-seq, and spatial transcriptomics, along with expertise in spatial transcriptomics platforms is highly desirable. Experience in high-performance computing or cloud-based environments will be an added advantage. We value strong analytical thinking, problem-solving capabilities, and organizational skills to manage multiple projects effectively. Exceptional communication and teamwork abilities are essential for fostering collaboration within our multidisciplinary research environment. A strong background in oncology, immunology, or related biomedical fields is advantageous, as is familiarity with advanced spatial omics analyses, multi-modal data integration, or machine learning approaches.

IFOM, the AIRC Institute of Molecular Oncology