Sanofi is one of the top pharmaceutical companies with more than 100,000 people 
in 100 countries. We recently built a multidisciplinary team focusing on using 
ML- and physics-based methods to accelerate design and engineering novel 
protein therapeutics.
https://sanofi.wd3.myworkdayjobs.com/SanofiCareers/job/Framingham-MA/Senior-Data-Scientist--Machine-Learning-for-Biologics_R2617876-1
https://sanofi.wd3.myworkdayjobs.com/SanofiCareers/job/Framingham-MA/Data-Scientist--Machine-Learning-for-Biologics_R2617878-1





Overview:
At Sanofi Large Molecule Research Platform, we have a strong ambition to 
utilize machine learning (ML) and artificial intelligence (AI) in all aspects 
in biologics discovery and development, with comprehensive programs spanning 
from deep repertoire mining to de novo design. Additionally, we are open and 
actively collaborate with leading biotech and academia. The new opening senior 
data scientist role is to seek a machine learning expert with strong expertise 
in modern data analysis methods, including NLP, graph, and 3D geometry-aware 
models. The successful candidate will work in an interdisciplinary team to 
apply cutting-edge computation, ML/DL, sequence-based and structure-based 
methods to resolve challenges in real-world drug discovery. This is an exciting 
opportunity to contribute to the process of design and engineering 
revolutionary biologics, including multivalent, multi-targeting molecules by 
leveraging large amount of proprietary data coming from our industry-leading 
high-throughput automation platforms. The successful candidate will gain deeper 
insight into drug development process and transform ML/DL algorithms into 
accelerating biologics discovery and development process, and make impacts to 
patients’ life.
Your responsibilities include:

  *   Evaluate and develop state-of-the-art computational methods to decode 
biophysical and geometrical features from antibody-antigen datasets and create 
predictive models for engineering.
  *   Develop and apply complex machine/deep learning solutions to our 
high-content and high-quality proprietary datasets, as well as public datasets.
  *   Perform data querying and feature extraction to improve current workflow 
for antibody/nanobody engineering, including affinity modification, 
cross-reactivity engineering, liability risk prediction and mitigation, 
multi-specific antibody engineering, and de novo antibody design.
  *   Maintain a keen awareness of recent developments in data science, 
bioinformatics, and state-of-the-art of ML/DL algorithms, aiming to accelerate 
development of new computational algorithms.
  *   Effectively collaborate with colleagues with diverse scientific 
background, identify problems and opportunities, combine computational and 
structural analysis to support large molecule projects.
Basic qualifications:

  *   Ph. D. in related field such as Biostatistics, Physics, Computation 
Biology, Biomedical Engineering, Computer Science, Applied Mathematics, 
Structural Biology with at least 2 years of experience or Master with at least 
5 years of relevant experience.
  *   Significant depth of expertise in ML/DL, hands-on experience with modern 
machine learning models, including Transformers, Graph NN, Recurrent NN, MLP 
etc.
  *   Sufficient in programing using deep learning libraries such as PyTorch, 
TensorFlow, and Keras. Experience with cloud computing, parallel computing, 
and/or supercomputing is expected.
  *   Track record of applying machine learning/ deep learning approaches to 
solve molecule-related problems. Familiarity with protein structure or sequence 
featurization and learned embeddings.
  *   Experience with database mining, big data, and large-scale virtual 
screening using Bayesian Optimization or Gaussian Processes is desired.
  *   Familiarity with Data Visualization tools/libraries and dimensionality 
reduction algorithms.
Preferred qualifications:

  *   Understanding of protein structure and protein-protein interaction. 
Experience with structural analysis and optimization of biochemical and 
biophysical properties, like thermodynamics, with protein design tools e.g. 
Rosetta, BioLuminate, or MOE, etc.
  *   Understanding of biologics R&D process is a plus.


Yu Qiu
Lab Head, Protein Engineering, Large Molecule Research
Digital Biologics Advanced Applications Lead, Digital Biologics Platform (DBxP)
Sanofi
[email protected]<mailto:[email protected]>
TEL.: 508-270-2555
3465 - 49 NEW YORK AVENUE - FRAMINGHAM – Massachusetts 01701
[[email protected]]

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