If you find science, speed, and helping address serious infectious diseases exhilarating, you have come to the right place.
Individually, were skilled, driven, and confident risk-takers. Collectively we're collaborative and accomplished. We're SuperNovas! Together we use our unique experiences, cultures, and learnings to turn innovation into reality while maintaining the highest standards. We value balance, encourage growth, and recognize that you are our most important asset. Build your future with us while bringing innovative vaccines to the world. We have a place for you!
Novavax, Inc (Nasdaq:NVAX) is a biotechnology company committed to helping address serious infectious diseases globally through the discovery, development and delivery of innovative vaccines to patients around the world. We have more than a decade of experience contending with some of the worlds most devastating diseases, and we are here to make a difference. Hard-won lessons and significant advances illustrate that our proven technology based on solid science tested by decades of research, has tremendous potential to make a substantial contribution to public health worldwide.
We are seeking a highly motivated and innovative Scientist with a Ph.D. in AI-ML, Structural Biology, computational biology, Molecular Biology, or a related field, to join our Vaccine translational sciences team. The ideal candidate will have a strong background in Artificial Intelligence machine learning (AI-ML) assisted protein antigen design, with demonstrated expertise in structure-based design, immunogen engineering, and translational vaccine development. This position offers the opportunity to work at the cutting edge of innovation, contributing to the development of next-generation vaccines targeting infectious diseases and emerging pathogens.
Key Responsibilities:
- Design and engineer recombinant protein antigens optimized for immunogenicity, stability, and manufacturability using emerging AI-ML and in-silico based methods.
- Use structure-based design approaches (e.g., homology modeling, cryo-EM/X-ray structural interpretation) to guide antigen and antibody discovery & development.
- Collaborate with protein chemists, molecular biologists and immunologists to assess antigen performance in preclinical models (e.g., ELISA, neutralization assays, B cell profiling).
- Work cross-functionally with other computational biologists, structural biologists, and immunologists in the team to iteratively improve antigen candidates.
- Interpret structural, biophysical, and immunological data to inform antigen design strategies.
- Present research findings in internal meetings and contribute to scientific publications and external presentations when needed.
- Contribute to patent applications and regulatory documentation for clinical development.
- Stay abreast of the latest developments in AI-ML, vaccine technologies, antigen design strategies, and immune escape mechanisms.
Qualifications:
- Ph.D. in either computational biology, AI-ML, Immunology, Structural Biology, Biochemistry, Molecular Biology, or a closely related field.
- 1 or more years of relevant postdoctoral or industry experience in protein antigen design or vaccine discovery. Exceptional candidates with no postdoctoral experience will also be considered.
- Strong knowledge of protein structure (X-Ray, CryoEM) and function, antigen-antibody interactions, and immune system principles.
- Proficiency in computational tools for protein modeling and design (e.g., Rosetta, PyMOL, AlphaFold, Chimera and large language models (LLM) in the context of protein design).
- Experience and familiarity with recombinant protein expression, purification, and characterization (e.g., SDS-PAGE, SEC, SPR, DSF), including structural biology methods CryoEM or X-Ray crystallography.
- Track record of scientific excellence as evidenced by peer-reviewed publications and/or patents.
- Strong analytical, organizational, and communication skills.
- Ability to work independently and collaboratively in a fast-paced research environment.
Preferred Qualifications:
- Experience with rational antigen-based vaccine design for viral (e.g., HIV, influenza, RSV, coronaviruses) and bacterial and other pathogens.
- Familiarity with AI-ML assisted softwares PyMol, Alphafold, epitope mapping, deep mutational scanning and simulation of molecular interactions, including large multi-complex protein heteromeric complexes.
- Experience working in a regulated (GLP/GMP) environment is a plus.