What You Will Contribute To Altos

San Diego Institute of Science is looking to recruit a Computational Scientist for collaborative research on the organization and function of complex biological tissues, in the context of homeostasis, aging, disease and rejuvenation. Altos Labs aims to foster creativity and progress in science, providing research groups with resources, and the freedom needed to pursue fundamental scientific challenges, including the ability to publish and present their work for wider scientific community. It is a highly collaborative research environment, and the Scientist will have an opportunity to contribute to the work of multiple groups, including laboratories of Peter Kharchenko, Robin Franklin, and Thore Graepel.

Responsibilities

The Scientist will be expected to:

• Collaborate with experimental groups to design, analyze, and interpret multi-omics data on homeostasis, aging, disease, and rejuvenation
• Develop new computational methods for analysis of single-cell and spatial-omics data
• Devise approaches to investigate cell communications, control of proliferation and cellular fates within human and animal tissues
• Analyze molecular determinants of cellular state, including epigenetic and regulatory mechanisms
• Bring computational and machine learning thinking to bear on Altos’ mission and challenges
• Continuously learn and stay up to date on the both biological and relevant computational literature to help generate new insights

Who You Are

We are open to candidates with a range of experience, as the position can be filled at the Scientist I, Scientist II, or Senior Scientist level. The level of the position will depend on the qualifications of the selected candidate.

Minimum Qualifications

• PhD in Computational Biology, Computer Science or a related discipline
• Track record of publications in peer-reviewed journals
• A strong interest in conducting genomics research in a highly collaborative setting
• Knowledge of statistical methods, probabilistic modeling techniques, and machine learning methods
• Excellent written and verbal communication skills; Ability to explain complex concepts to researchers outside of your immediate field
• Good organizational skills to effectively move forward collaborative projects
• Ability to thrive in collaborative scientific environments, come up with original and pragmatic solutions

Preferred Qualifications

• Track record of analysis of genomic data, including RNA, chromatin and DNA modifications, and proteins
• Knowledge of single-cell analysis methods
• Experience in developing tools in R or python, and experience with relevant repositories
• Working knowledge of a subset of the following: deep learning techniques, variational optimization, generative models, graph neural networks
• Familiarity with multi-omics integration or spatial transcriptomics analysis

Salary Range: Scientist I; $127,500 - $172,500 | Scientist II; $150,000 - $228,800 | Senior Scientist $176,000 - $288,000

Exact compensation may vary based on skills, experience, and location.

#LI-KM1