AbCellera is a young, energetic, and rapidly growing biotech company with an amazing team that searches, decodes, and analyzes natural immune systems to find antibodies that its partners can develop into drugs to prevent and treat disease. We are seeking a highly motivated, independent Senior Scientist to help expand the role of structural modeling techniques for protein engineering applications. The ideal candidate will have a proven track record of design and implementation of structural modeling algorithms and strategies, with broad knowledge of the state of the field. We need someone who is an independent thinker, and can work collaboratively with a diverse team of experimentalists, engineers, and mathematicians to develop creative solutions to protein engineering challenges. This is an excellent opportunity to apply computational modeling expertise in a high impact, real-world setting.
How you might spend your days:
- Building, maintaining, and expanding a modern and scalable structural modeling infrastructure
- Implementation and evaluation of structural modeling algorithms and techniques
- Collaborating with teams across the company to understand protein engineering challenges and propose solutions
- Training and mentoring more junior scientists
- Preparing and authoring materials to educate colleagues, and communicate strategies, key findings and implications
We’d love to hear from you if:
- You are strongly self-motivated and work independently to identify project needs and follow that up with building and implementing solutions
- You have strong opinions about the role of structural modeling as a protein engineering tool
- You are excited about the opportunity to build and deploy computational tools towards real-world drug discovery problems
Required qualifications and experience:
- A PhD in Computational Biology, Structural Biochemistry, or related field and 2-3+ years of industry experience
- Experience working with a modern computational development environment; including data analysis, cloud-based high performance computing, and collaborative software development tools
- Strong interpersonal skills with the ability to work collaboratively as a member of cross-functional team
- Excellent verbal and written communication skills, including public presentation of complex data
- Developed computational tools that have been directly applied to high-throughput protein engineering efforts
- Familiarity with Python data analysis (Numpy/Pandas/Dask) and modern machine learning (PyTorch/Keras/Tensorflow) stack is preferred
- Familiarity with the Rosetta molecular modeling suite is preferred
Offers & benefits:
- The opportunity to work with an inspired team on challenging problems that matter
- An attractive compensation package, including health and lifestyle benefits
- A minimum of 3 weeks’ vacation
- Opportunities for personal and professional development
At AbCellera, we’re solving tough problems and creating innovative solutions from the ground up - custom immunizations, microfluidics, high-throughput imaging, genomics, computation, machine learning and laboratory automation. We’re revolutionizing how our scientists can explore antibodies and the scale at which they can do so. This is life-changing research and you could be a part of it.
You’ll join a diverse and multi-disciplinary team of biologists, biochemists, engineers, bioinformaticians, computer scientists and physicists - all working together to bring better therapies to patients. We’re a growing company with a high-throughput pipeline and the drive to be the best in the industry. This isn’t just about having the best technology. We know we need a world-class team of visionaries and innovators. We look for people with drive and energy. Idealists. People we love and people we trust. This may be unconventional, but it is the key to our success. We’re looking for someone like you to help us get there.
Please submit your application through our website and refer to Job ID 21238 in your cover letter. We apologize in advance, but we receive a large volume of applications and are only able to contact those who are selected for an interview.