The Computational Geneticist is a member of the Statistical Genetics team, which is developing a groundbreaking platform to discover the genes underlying human disease from genome-wide association studies (GWAS).
The platform is described here: https://www.biorxiv.org/content/10.1101/2022.04.28.489887v1.
The Statistical Genetics team works collaboratively with our colleagues across the company to identify, validate, and develop novel therapeutics that target the root causes of disease, as revealed by human genetics. We are seeking a brilliant, highly creative computational scientist to join the team, to help advance the state of the art established by our platform and to extend it into new applications. Candidates should be skilled software engineers and applied mathematicians, with a passion for computational and scientific work that solves major challenges in human health. Successful candidates must be able to work effectively both in a collaborative setting and independently while possessing outstanding written, visual, and oral communication skills.
- Work collaboratively with other applied mathematicians and software engineers to develop the theory and source code to extend the Human Genetics Platform (HGP) in new directions
- Develop, test, and deploy new software for the HGP
- Contribute to UI and web development to expose the results from the HGP to scientists within the firm and potentially to external collaborators/partners
- Participate in code reviews, software deployment and maintenance, iteration planning and timeline estimation, and software design discussions
- Contribute to running the HGP over a distributed computational architecture in the cloud
- Propose new directions of research to leverage the HGP, either to find new drug targets or to apply the platform in entirely new ways
- Summarize and present key findings to mixed audiences of experimental biologists, theoreticians, chemists, and physicians
- Identify and propose novel disease genes that are candidates for therapeutic development in diseases of high unmet need
Qualifications and Education Requirements:
You must have:
- Ph.D. in Computational Biology, Statistical Genetics, Physics, Applied Mathematics, Computer Science, or a related discipline
- Expertise in scientific programming, preferably in R, Python, or C++
- Commitment to rigor, in both quantitative analysis and software development
- Excellent interpersonal, communication, and collaboration skills
Additional preferred experience includes:
- Experience writing software on a team, with version control (preferably git) and code reviews
- Familiarity with the Linux operating system
- Programming experience in R, Python, and C++
- Working knowledge of Amazon Web Services (AWS)
- A firm understanding of the principles of object-oriented programming, especially in C++
- A strong background in pure or applied mathematics
- Knowledge of biology, genetics, and the molecular mechanisms of human physiology
Kallyope is a clinical-stage NYC-based biotechnology company focused on the gut-brain axis. The company, founded in 2015 by Tom Maniatis, Richard Axel, and Charles Zuker, leverages leading technologies to map the hormonal and neural circuitry between the gut and other organs, including the brain, and translate new discoveries into novel therapeutics. Our cross-disciplinary biotechnology team has built a platform integrating single cell and single nucleus sequencing, computational biology, neural imaging, cellular and molecular biology, and human genetics to provide an understanding of gut and gut-brain biology which, when coupled with our deep drug discovery expertise, will lead to therapeutics in multiple areas of high unmet need. The Company has two lead programs in clinical development, one targeting metabolic circuits for diabetes and obesity, and the other focused on restoration of GI barrier function for IBD and other disorders associated with a defective barrier. The company has raised $479 M in 4 rounds of funding from several leading biotech investors. For more details, see https://kallyope.com.