mRNA Principal Data Scientist, Computational Chemistry - All Genders
- +3
- +8
- France
- +3
- +8
- France
About
Job title: mRNA Computational Chemistry Principal Data Scientist (M/F)
About the Opportunity
As an experienced mRNA Data Scientist and Computational Chemist, you will lead data analysis, ML, and molecular modeling efforts for design and optimization of best-in-class mRNA vaccines and therapeutics as part of the Data and Computational Science team in the mRNA CoE. This team brings end-to-end data integration and advanced analytics (pre-clinical, biomarkers, process development, CMC, clinical) in the mRNA CoE. Deploying and exploiting digital solutions (AI/machine learning, data, analytics, chemoinformatics) to integrate the full data value chain, extracting actionable information for a move to a full data-driven strategy, and decision-making process, to increase the probability of success and to accelerate mRNA vaccines and therapeutics development and launch. In this position, you will work in collaboration with other mRNA CoE platforms scientific and technical experts located in the US and in France, bringing practical knowledge and experience in combining Machine Learning (ML) and molecular modeling methods for design and optimization of mRNA vaccines and therapeutics. We look for scientists with deep expertise in the mathematics and theoretical underpinnings of machine learning and computational chemistry (cheminformatics, molecular dynamics, QSAR), with a deep knowledge and experience in biophysics/biochemistry.
KEY RESPONSIBILITIES FOR POSITION
In this role you will
- Collaborate with stakeholders and other group experts in the development and execution of the scientific strategy and technical solutions to develop best-in-class mRNA vaccines and therapeutics
- Be responsible for identifying, setting strategy and delivering 1 to 2 end-to-end ML data science projects for design and optimization of mRNA sequences and formulations and predict performance for vaccines and therapeutic applications
- Act as a scientific expert and partner in the fields of molecular biology/biochemistry/biophysics, chemoinformatics and AI/ML
- Design and assess studies to evaluate the performance of mRNA vaccines and therapeutics. Translate experimental learnings into the development and refinement of computational models for design, optimization, selection, and formulation of mRNA vaccines
- Develop and evaluate computational and statistical methods for data analysis
- Responsible for designing, prototyping, and validating computational solutions to diverse scientific challenges in the fields of mRNA vaccines and therapeutics
- Develop, deploy, and assess the results of at-scale models at varying levels of model granularity encompassing heterogeneous preclinical and clinical data
- Employ machine learning methods such as deep learning, neural networks, reinforcement learning, graphical and generative models to deconvolve high-dimensional experimental and in silico modeling results
- Employ molecular modeling techniques with a focus on molecular physicochemical descriptors, molecular dynamics, QSAR models, and virtual screening for properties prediction, molecular mechanism elucidation, and data-driven design of biomolecular systems.
- Maintain a well-documented, reusable codebase, and traceable model history
- Maintain awareness of the latest developments in relevant fields, evaluate and apply as warranted
- Generate IP and participate in the drafting of patent filings
- Prepare and publish scientific papers and congress reports
- Demonstrate good software engineering practices
- Proactively identify, assess, and internalize emerging technologies and methods
COMPETENCIES/REQUIREMENTS FOR POSITION
About you
- PhD in computational biology/medicinal chemistry or related field with expertise in machine learning, biochemistry, and molecular modeling. 3+ years post-doc experience including project leadership; preferably in industry
- Deep knowledge and experience in computational methods applied to biology/biophysics/biochemistry scope
- High proficiency in molecular modeling (chemoinformatics, molecular dynamics and CADD software) and machine learning (Deep Learning, Graph Embeddings, Reinforcement and Transfer Learning) and algorithmic analysis of data
- High proficiency in Python/R, molecular modeling, and machine learning libraries (RDkit, deepchem, Schrodinger, Gromacs/NAMD) and cloud computing.
- Practical experience proposing, prototyping, and deploying novel algorithms; developing and validating new models
- Demonstrated record of transforming algorithms/theory into practical applications delivering robust models that are high performance, interpretable and actionable
- Experience with software development good practices (code versioning, testing, etc.)
- A creative problem solver, skilled in divergent thinking and turning complex data into actionable insights and knowledge
- Good communication scientific writing and presentation skills, ability to simplify complex problems and communicate complex solutions in a simple and effective manner
- Good networking skills and fluent interactions with one or more scientific communities
- Understanding of vaccine development processes is a plus, especially having domain expertise or familiarity with RNA processes, drug delivery using Lipid Nanoparticles (LNPs), and RNA-centric techniques/methods
- Fluent in English (French is a plus)
Nice-to-have skills
- Machine Learning
- Data Analysis
- Deep Learning
- Neural Networks
- Python
- R
- Cloud Computing
- Software Engineering
Work experience
- Machine Learning
- Computer Vision
- Data Scientist
Languages
- English