Computational Systems Biologist
Multiomics | Systems biology | Causal reasoning | Network inference | Precision Medicine | Mechanism of action deconvolution | Machine learning | Product development
Fully remote | Top quartile salary | Stock options | 401K | Health, dental and vision insurance
We are hiring an innovative computational biologist to develop systems biology approaches within the Syntensor platform, a collaborative, self-service, cloud-based platform that leverages predictive models and complex data to explain drug efficacy and toxicity. Fully remote. We are looking for a systems biologist who can improve upon the existing scientific capabilities of our platform in the areas of mechanism of action deconvolution, visual pathway exploration, and biomarker identification.
The role
- Implement omics-based methods to improve our mechanism of action deconvolution algorithms and provide testable hypotheses explaining drug efficacy and toxicity
- Develop approaches to network inference to create cell- and tissue-specific signaling networks
- Improve the pathway data in the Syntensor graph and collaborate with the product team to implement novel pathway and network visualizations in the user-facing app
- Leverage systems biology approaches to identify predictive biomarkers that characterize drug response
- Collaborate with bioinformatics scientists, machine learning researchers and software developers to understand requirements for data assets in the Syntensor platform
- Competitive compensation - A starting salary in the top quartile for role and level, based on local benchmarks
- Stock options - you are joining an early-stage startup we want you to have ‘skin in the game’ and your options package will reflect this
- Self-manage - we are a distributed-first company, working from home and collaborating asynchronously from Seattle, NY, Vermont, and Manchester
- Take on a grand challenge and share our purposeful mission - we’re building a biological systems simulator that will transform how medicines are developed - you will be making it accessible and powerful for scientists and doctors, with a big downstream impact on the wellbeing of millions of patients
About you
- Ph.D. in Bioinformatics, Computational Biology, Genomics, or a related field.
- Minimum of 1-2 years of post-PhD experience in bioinformatics with a focus on leveraging multiomics and biological network data in developing systems biology approaches to characterize the cellular state in disease or following chemical/genetic perturbation
- Experience with programming in Python
- Extensive hands-on experience with high-throughput sequencing data, including whole-genome, exome, and RNA-seq.
- Strong domain expertise in systems biology datasets such as interactome datasets and pathway databases, like Reactome
- Familiarity with publicly available omics datasets and repositories such as TCGA
Nice to haves
- API development in python
- Experience applying for access to datasets in dbGaP
- Familiarity with the drug discovery and development process
About us
Our mission
We are on a mission to provide access to more effective medicines for millions of patients. We’re building a model of human molecular physiology for research scientists and clinicians that can answer the fundamental question, "will it work?"
Every modernized field of engineering has a systems simulator to test complex interactions in bits rather than atoms. This doesn’t yet exist for biology. Without one, drug development is expensive because risk of failure is very high; 30-60% of prescribed medicines have no clinical benefit to patients and adverse reaction to treatment is the 4th leading cause of death in the US, ahead of pulmonary disease and diabetes. Syntensor is taking on this grand challenge, developing fundamental machine learning methods and applying them at scale to biological data so every individual patient can be prescribed the most effective, least toxic treatment possible.
What we do
We are productionizing and scaling up a generalizable machine learning platform that predicts efficacy and toxicity for any drug in any indication. We are using an extensive, heterogeneous biomedical graph, novel fundamental ML methods and advanced engineering infrastructure to generate and explain model outputs for users of our app. Currently, our users are research scientists involved in drug development.
The team
We are a small team of people with diverse skills and a shared bias towards problem solving and execution. We are inventors and builders who believe in the scientific method; feedback and iteration is essential to our process and we share our work early and often. That said, we aim high. Our mission and the domain in which we operate demand that we take on some of the hardest problems researchers, scientists, engineers and designers face, and we are determined to build technology that solves them properly and usefully for users of our platform. We are looking for talented people who are motivated by the challenge of hard problems and who are already curious about the technological, scientific or cultural domains with which we engage.
We are a distributed-first team and very relaxed about where and when work happens, but come together as a whole team weekly to sync-up. We work with intrinsic curiosity and motivation towards well defined goals (even where there are unknown unknowns). Our diversity, great communication and respectful, supportive teamwork make us highly effective.