About the team

In my lab, we are passionate about science but also want to have fun while doing it. We strive to keep the lab a fun and supportive place where people can learn and thrive. The entire lab meets weekly for lab meetings, where we discuss internal work or external papers. I meet with my PhD students weekly. At the start of your PhD we will have a detailed discussion of your long-term career goals, and we will design your PhD project around helping you achieve these goals.

We will select and design a thesis project that is of mutual interest. Generally, projects will be more top-heavy (e.g. ideated by me) to start, with the benefit being that these projects will have a high likelihood of success and are thus “safer” as a PhD project. However, over time and as you gain experience, you will have the opportunity to lead new research directions as well.

Research Focus and Collaborators

Viruses evolve more rapidly than any other biological entity, leading to the emergence of hundreds of millions of viral proteins with no known function. The Nomburg Lab combines computational biology, virology, molecular biology, and artificial intelligence to understand the function of these viral proteins. We have a special interest in understanding how viral proteins interfere with cellular immunity. We are also interested in the conserved mechanisms used by cells for viral sensing. In collaboration with the robotics lab, we establish highly automated, scaled assays to test our predictions, and use these data to train new predictors of viral protein function.

Candidate’s Profile and Skills

Projects are diverse and include both computational and experimental components. We’re interested in both backgrounds, so this is a great opportunity to learn new things!

Prior experience and background with either computational methods or experimental methods is required. You don’t need to have background in both.

Computational background includes: Experience with bash, R, and/or python ; experience operating on a high-performance computing cluster or on cloud computing ; experience leading a bioinformatics project from start to finish. Experience with protein structure prediction, phylogenetics, or related skills isn’t required but is a bonus!

Experimental background includes: Experience with molecular biology, biochemistry, and/or cell biology ; experience leading an experimental project in the lab; experience with robotics and automation isn’t required but is a bonus!

Project 1: Characterization and discovery of viral immune antagonists

We use bioinformatics methods to discover new viral immune antagonists, with a special interest in those that are recurrently used by diverse viral families. We test our predictions using automated immune signaling assays and use these data to build predictors. We are also very interested in how conserved immune antagonists evolve.

This project will be roughly 50:50 computational and experimental.

Project 2: Characterization of viral protein diversity and function

Viral proteins are highly diverse and are expressed using complex patterns of transcription and splicing. We will be incorporating RNA sequencing data with protein structure prediction to study how transcriptional variation can expand the structural and functional landscape of viruses.

This project will be 80% computational.

Project 3: Viral enzyme landscape (Joint with Ariane Mora)

Many viral proteins have unclear functions. Under the join supervision of Ariane Mora, we will systematically predict, identify, and test novel enzymatic functions hidden in existing viral proteins. We’ll use these predictions to understand viral pathogenesis and as a source of useful enzymes for biotechnology applications.

This project will be 60-70% computational.