Background & Skills
Academic path, technical expertise, and professional experience.
Professional CV
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Academic CV
I was lucky enough to attend, as part of an Erasmus program, courses in Neurogenomics and brain disease modelling, Functional biology, Developmental biology, Genetics, Cellular and molecular biology and Bioinformatics.
These courses allowed me to acquire greater knowledge in molecular and cellular biology, which is an essential framework for a bioinformatician.
My training at EIDD Paris gave me the biological framework necessary for any bioinformatician through courses such as Molecular and cellular biology, Biochemistry and Biophysics. Computer training includes Biostatistics, Machine learning with Python, and Algorithmic with C and Java.
- Group project: C++ algorithm to list biochemical interactions during protein folding — pipeline takes a PDB file as input and outputs a table of probable biochemical interactions and their type.
- Individual project: machine learning (dimensionality reduction and clustering) on brain cancer MRI images from Kaggle to identify cancer types by morphology.
Studied Mechanics, Fluid Mechanics and Design, acquiring bases in solid mechanics and the mathematical equations that govern them. Attended introductions to General Thermodynamics and Energetics.
Preparatory class MPSI then PSI — solid foundation in scientific reasoning through mathematics, physics, solid mechanics, thermal diffusion, particle diffusion, thermodynamics, thermochemistry and linear algebra.
Objective: integrate PDAC spatial data into a PhysiCell model. Modelled a first version of a tumor microenvironment model (TME) using PhysiCell (agent-based), simulating biological phenomena such as EMT, hypoxia and immunosuppression.
Analysed immunofluorescence data and Imaging Mass Cytometry via Tysserand and MOSNA — two Python packages specialized in the generation of spatial networks from biological tissue data and their statistical analysis.
Studied genetic variants in the 5'UTR region as a cause of familial dyslipidaemia through mutation analysis of the LDLR, APOB, APOE, PCSK9 genes — responsible for cholesterol regulation and LDL. Annotated variants with the MORFEE pipeline (R, David-Alexandre Trégouët, Inserm Bordeaux).
Set up MORFEE on the BiRD computing cluster in Nantes; developed a Python and Nextflow pipeline encapsulating MORFEE, enabling analysis of VCF/BCF files of any size for any gene in the human genome. Parallelized on 32 threads, treating mutations from more than 200,000 UKBioBank patients across 20,000+ genes.
Conducted statistical tests to verify result significance; generated Manhattan and Forest plots explaining the potential impact of isolated variants on LDL-C rates at birth.
O. Griere, M. Bernard and V. Pancaldi. Using PhysiCell modelling to simulate the PDAC tumor microenvironment response to therapies based on patients' spatial omics data.
Poster presentation at JOBIM (French bioinformatics conference) 2025, Bordeaux 8–11th July 2025.
Restocking the store, checkout, customer reception.
Creation of partnerships with the municipal administration and development of free workshops for young people in the priority neighbourhoods of Villiers-le-Bel.