United States onlyWe are currently looking to hire a Bioinformatician / Computational Biologist to analyze and mine genome-wide next generation sequencing datasets (such as single cell and bulk RNAseq data, ATAC-seq data, etc) to gain insights into stem cell & ovarian cell biology. You will collaborate closely with a group of talented bioinformaticians to deliver scientific results and data visualizations, as well as with bench scientists to analyze ‘omics data for a broad range of projects. Routine work includes running and maintaining automated bioinformatics pipelines, which include QC assessments, differential expression and data visualization components. Understanding how to interpret complex low input datasets for biological utility and translate findings back to the bench is a key requirement. You will collaborate broadly with biologists to identify ways in which to leverage our computational data towards new hypotheses and scientific directions that can then be tested in the lab. Your work would include many opportunities to find custom solutions to interesting biological problems.
Our mission
Conception is a startup with the mission of generating viable human eggs from induced pluripotent stem cells (iPSCs). Successful development of our research could have many benefits, such as removing age limits on motherhood, allowing for easy screening of eggs with harmful genetic mutations, and allowing same-sex couples to reproduce. This has been done in mice, and now we are working to translate it to humans.
Our research
To accomplish our goal, we must derive human germ cells from iPSCs (human germ cell-like cells, hPGCLCs) that resemble both the transcriptional and epigenetic profile of in vivo germ cells (PGCs) that are able to enter meiosis and develop to viable human eggs. We create ovarian organoids from primary cells and stem cell derived cells to help the eggs develop properly.
Tasks & responsibilities:
Functionally interact with core Conception computational infrastructure including databases, automated pipelines, HPC cluster, etc
Contribute to team code bases, using best practices for documentation and version control
Work with biology teams to independently perform team-specific analysis projects using both in-house & publicly available data
Required skills/experience:
PhD in computational biology, genomics, systems biology or related field or masters + 1-3 years of industry experience.
Highly proficient in R, python, and bash
Highly proficient in analyzing RNA-seq data, including experience with single cell RNAseq packages/workflows/algorithms.
Excellent foundational data analysis skills (understand how to clean/QC data, grasp of basic statistical principles, generate hypotheses and 'smell test' data before returning a result)
Highly proficient in building and running automated preprocessing workflows for a variety of data types including (sc)RNAseq or ATAC-seq
Proficiency in versioning and collaborative coding via git
Strong ability to devise, scope, and execute data analyses independently
Prior experience translating computational findings into testable hypotheses and experimental designs
Strong communication skills, particularly with diverse audiences
Prior experience with a high performance computing cluster and/or cloud computing environment
Preferred skills/experience:
Prior experience with iPSC derivation & germ cell biology preferred
Knowledge of relevant bench techniques is beneficial
Experience with spatial transcriptomics
Come and work with us
We are well-funded and connected in Silicon Valley, offering competitive pay, equity, excellent healthcare benefits, and a collaborative research environment focused on meaningful results.
If you are passionate, hardworking, and aligned with our mission, we want to hear from you!
To learn more about us, our mission, and approach you can read two features published by The New Yorker and MIT Technology Review.
