Frame the decision
Research trained me to turn open-ended questions into hypotheses that can be tested.
HEALTHCARE STRATEGY · INNOVATION · AI
I combine AI
and scientific judgment
to inform decisions.
Pharmacist · PhD in computational structural biology
HEC Paris MBA candidate
My background connects pharmacy, computational biology and AI. Through an HEC Paris MBA, I am expanding that perspective to business, with a particular interest in embedding AI approaches into healthcare strategy and decision-making.
Sanofi Life Sciences Scholarship
Based in the Paris regionFR · EN · AR
SCIENCE → HEALTHCARE STRATEGY
Connecting scientific insight with healthcare decisions.
I am interested in how scientific evidence, data and AI can inform healthcare strategy—from understanding opportunities to assessing value and shaping products. I enjoy conversations across strategy, transformation, market access and product teams.
How my experience connects +
Compare the evidence
I analyse data, examine model uncertainty and explain what a result can—and cannot—support.
Build the business perspective
The MBA is where I develop the business perspective to connect scientific evidence with market, organisational and financial questions.
01 — CONTRIBUTION
What I bring
Connect AI predictions with scientific judgment
At Institut Pasteur, I implemented workflows combining AlphaFold predictions, uncertainty and biological reasoning to guide exploration of alternative conformations.
Evidence: implemented research workflows.
Turn complex data into usable evidence
My doctoral work analysed 977 protein–RNA interfaces and 2,022 comparable pairs, with a first-author publication in PLOS Computational Biology.
Evidence: peer-reviewed analysis, software and visualisation.
Make knowledge accessible
I co-developed RNAPROTDB so researchers can explore protein–RNA interaction data through an interactive web platform.
Evidence: a publicly accessible research tool.
Research evidence: AI and scientific judgment +
AI + SCIENTIFIC JUDGMENT
Predict. Examine. Refine.
My approach is iterative: model outputs inform scientific questions, and scientific assessment shapes the next modelling step.
Generate predictions
Use AI models within a defined biological question.
Examine the evidence
Compare with biological knowledge and inspect uncertainty and alternative explanations.
Guide the next iteration
Use that assessment to refine what to explore next.
Grounded in computational structural biology and AlphaFold-based research.
Postdoctoral research: data, AI and simulation +
Host–pathogen interaction database
I constructed a database of host–pathogen protein–protein complexes to support their systematic analysis.
Using AI uncertainty to explore alternative conformations
Across seven molecular systems, I incorporated uncertainty information from AlphaFold outputs into molecular dynamics simulations to explore alternative conformations.
What this demonstrates
Database construction, comparative structural analysis and integration of AI outputs into scientific workflows. These projects inform how I assess evidence and decide what to investigate next.
Technical toolkit
Python and R for data analysis and visualisation; Jupyter notebooks for computational exploration.
Research evidence: structural similarity +
RESEARCH → REASONING
Look beyond the apparent similarity.
Schematic illustration · not research data
I investigated how structural similarity can support predictions of molecular interactions when protein sequences diverge—and where that inference becomes unreliable.
The question, my contribution and the result +
The question
When protein–RNA complexes are related, which molecular contacts remain similar—and which change?
My contribution
Data curation, computational analysis, software and visualisation within a collaborative research project.
The result
The study found that spatial contacts were more conserved than polar interactions, including in distant relatives. This provides evidence for template-based molecular modelling.
What I take into decision-making
Test what transfers, expose what does not, and explain the limits before recommending a next step. It is the approach I bring to new problems.
PLOS Computational Biology · 2024 ↗ Explore my doctoral thesis ↗02 — MY APPROACH
How I work
Learn what the problem requires
I moved from pharmacy into coding and bioinformatics, graduated first in my 2018–2020 master’s cohort after changing countries, then developed a doctoral topic new to my laboratory.
Make uncertainty useful
In my AlphaFold-based work, uncertainty became an input to exploring alternative conformations rather than something to hide.
Adapt the explanation to the audience
I worked with medical and non-medical colleagues and ran coding, mathematics and physics workshops for children through science outreach.
03 — MY BACKGROUND
A scientific foundation.
An expanding perspective.
FOUNDATIONS
PharmD + MSc
MSc · 2018–2020Pharmacy & bioinformatics
A clinical foundation, extended into programming and data analysis.
Show more +
DOCTORAL TRAINING
PhD
2024AI & structural biology
977 protein–RNA interfaces analysed to explore molecular interactions.
Show more +
RESEARCH
Institut Pasteur
Since 2025Structural bioinformatics
Integrated AlphaFold predictions and uncertainty into computational workflows.
Show more +
BUSINESS EDUCATION
MBA — HEC Paris
Since September 2026Full-time MBA
Building business and strategy expertise on a foundation in science and AI.
Show more +
BUSINESS EXPOSURE
Spot the opportunity. Build the response.
Hands-on experience in a family business: marketing, responding to customer demand and building supplier partnerships.
My commercial experience +
Responding to demand over two years
In a family business in Algeria, I helped adapt marketing and organise supply partnerships over two years when customer demand exceeded our own capacity.
Prospecting & lead qualification
Familiarity with identifying potential customers, understanding their needs and assessing the relevance of a commercial opportunity.
Partnerships & execution
Worked with external suppliers and collaborative arrangements to meet demand and support business growth.
MISSION
Better decisions. More voices in science.
My mission is to connect science, AI and healthcare decisions—and empower women in science to have a stronger voice in shaping them.
I want to help scientific evidence inform business choices so good science has a better chance of reaching patients. Supporting women’s progression from scientific expertise to influence and leadership is part of that ambition.
I’m interested in contributing to science outreach, workshops and conversations about women’s progression in science.
RESEARCH & COMMUNITY
Work you can explore
Doctoral thesis
Computational structural biology · CEA / Université Paris-Saclay · 2024
Explore my doctoral thesis ↗First-author publication
Protein–RNA interface conservation · PLOS Computational Biology · 2024
Read the paper ↗RNAPROTDB
An interactive platform I co-developed to explore research data.
Explore the tool ↗Healthcare Club Ambassador
HEC Paris · Connecting my scientific background with conversations about healthcare and business.
LET’S CONNECT
Let’s talk.
I’d be happy to connect and exchange perspectives on careers and opportunities in healthcare.
ikram.mahmoudi@hec.edu ↗Mon–Sat · 09:00–20:00 (Paris), subject to availability
◷20 minutes to start↗Remote, in French or English
im.
Ikram MahmoudiHealthcare · Innovation · AI
✳AN INTRODUCTORY CONVERSATION
Let's find a moment
to talk.
Online scheduling will be available soon. In the meantime, send me a message on LinkedIn and we can arrange a time.
Connect with me on LinkedIn↗No appointment is booked at this stage.