Computational Structural Biologist

Job summary
Permanent contract
Salary: Not specified
Starting date: September 01, 2024
A few days at home
Experience: > 1 year
Education: Master's Degree
Skills & expertise
Generated content
Positive attitude
Machine learning

Whitelab Genomics
Whitelab Genomics

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Questions and answers about the job

The position

Job description

Dive into the future of healthcare, where you’ll play a crucial role in revolutionizing genomic medicine with AI and leave a lasting impact for generations to come.

WhiteLab Genomics was founded with the belief that life-saving drugs should be accessible to all patients in need. United in our vision, we’ve become a part of Y Combinator, French Tech 2030, Future 40 by Station F, and we’ve been recognized by The Galien Foundation (”Best Startup” category), among other institutions at the forefront of technology. Today, we strive to become the leading expert in A.I. for genomic medicine, operating as the go-to partner for research and development.

Our Structural Biology Team elucidates intricate molecular structures essential for genomic therapies, providing valuable insights into target identification, protein-ligand interactions, and structural optimization. Using cutting-edge techniques and computational methods, we investigate the three-dimensional structures of biological molecules.

In this dynamic role, you’ll design and execute modelization tasks for WhiteLab Genomics’ projects. Your contributions will be pivotal to advancing our cell and gene therapy platform, and your day-to-day tasks will molecular modeling, protein design, and cutting-edge machine learning and deep learning algorithms applied to structural biology.

Our Core Values:

We Believe that Care is Everything.

We Value our Collective Potential

We Cultivate Proactive Communication, Clarity and Respect

We Have a Can-Do Attitude

We Strive for Excellence

Preferred experience

We’re Eager to Meer You If…

  • You have a Ph.D in Structural Bioinformatics, Genomics, Computational Chemistry, Data Science or another relevant area or Master’s Degree in Structural Bioinformatics, Machine Learning, Computational Biology, or another relevant area, plus applied experience.

  • You have experience in structural prediction for proteins, protein language models, peptide modelling, mutation effects analysis, protein-protein interaction modelling, or biophysical problems, like ligand-receptors challenges. Experience in AI applied to drug design would be a plus!

  • You have extensive experience in Computational chemistry / structural bioinformatics applied to drug design. Machine learning learning would be a plus.

  • You’re proficient in Python, Bash, or R. Being familiar with standard graph machine learning libraries applied to drug design is a plus.

  • You possess excellent verbal and written communication skills, with the ability to convey complex technical concepts to both technical and non-technical audiences.

  • You have honed your interpersonal skills, which gives you the ability to collaborate effectively with cross-functional teams

Here’s How You’ll Make an Impact…

  • You’ll design and execute new modeling tasks for WhiteLab Genomics’ projects, including contributing to the development of our cell & gene therapy platform by using molecular modelling, protein design and machine and/or deep learning algorithms applied to structural biology

  • You’ll participate in various scientific projects related to gene therapies, while working on R&D development and knowledge extraction from scientific literature and/or databases

  • You’ll collaborate with our engineers to conduct rigorous data analysis and statistical modeling, ensuring clear and efficient communication of results internally and externally

  • You’ll stay up-to-date on the latest developments in both structural biology and AI applied to structural biology and relevant applications

  • You’ll write high-quality, maintainable, and modular code with concise documentation

  • You’ll monitor emerging technologies and trends, assessing their viability and potential integration into our platform and operations

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