Stagiaire Translational Sciences Rare diseases/NeurosciencesIPSEN

Job Title: Master's Student - Proteomics & Pathway Analysis Internship

Duration: 6 months
Location: Balard
Department: Early Development/Translational Sciences
Reports to: Luis Briseno-Roa (coll. Jacquie Maignel)

Overview

We are seeking a motivated Master's student to join our team for a 6-month internship focused on supporting the analysis of a proteomic study conducted on samples from a phase 3 study in rare liver disease. This role offers an excellent opportunity to gain hands-on experience in bioinformatics, pathway analysis, and scientific communication within a cutting-edge research environment.

Key Responsibilities

• Literature Review: Conduct comprehensive bibliography searches to identify relevant scientific publications and contextualize findings.
• Pathway Analysis: Utilize pathway analysis software tools to interpret proteomic data and identify biological mechanisms.
• Statistical Exploration: Investigate statistical aspects of the study to support data interpretation and robustness.
• Scientific Narrative Development: Contribute to drafting a narrative on the mechanism of action of the drug in Primary Biliary Cholangitis (PBC).
• Communication Support: Participate in the preparation of internal and external scientific communications, including presentations and potential publications.

Expected Deliverables

• A detailed narrative describing the mechanism of action in PBC based on proteomic data and literature.
• Contributions to internal reports and potential external scientific communications (e.g., posters, abstracts).

Qualifications

• Currently enrolled in a Master's program in Life Sciences, or a related field.
• Basic understanding of statistics and data interpretation.
• Strong analytical and problem-solving skills.
• Good written and verbal communication skills in English.

Preferred Skills

• Knowledge of nuclear receptors or liver diseases is a plus.
• Familiarity with proteomics data analysis and pathway analysis tools (e.g., Ingenuity Pathway Analysis, Reactome, or similar) is a plus.