Epigene Labs is a pioneering techbio company focused on implementing augmented intelligence in precision oncology. We are seeking a strongly motivated Computational Biologist eager to leverage their skills in our fight against cancer.

As a member of the computational biology team, you will have a pivotal position and will collaborate closely with an interdisciplinary team.

This position encompass the following activities

• Design, prototype, and implement pipelines for automatic integration and normalization of cancer transcriptomic data, as well as other high-throughput molecular data types ensuring data quality and performance

• Develop robust and flexible and analysis workflows and bioinformatic tools to process different types of NGS data

• Develop bespoke algorithms for combining and prioritizing the results we generate

• Document, summarize, and communicate results in various settings, including management meetings and, on occasion, scientific conferences

Required

• Ability to implement and benchmark computational methods from the fields of biostatistics and bioinformatics

• Experience in end-to-end pipeline implementation for data management

• Experience in the analysis and interpretation of multiple types of NGS data (RNA-Seq, DNA-Seq, scRNA-Seq)

• Strong programming ability in python

• A team player with the ability to also work autonomously, and who has a lifelong learning mindset

• Outstanding interpersonal and English communication skills

Preferred

• Experience integrating multi-omics data is a plus

• Experience working in cloud environments such as AWS, Azure

• Experience with mining publicly available databases (GEO, TCGA, etc.)

• Experience with version control systems (Git) and development good practices (unit testing, CI/CD)

Education and experience

• P.h.D. or Master’s degree in Computational Biology, Bioinformatics, or related technical fields with 2/3 years of experience

• Working knowledge of healthcare, biopharma and/or oncology is a plus

• Initial fit call with the computational biology lead.

• Technical challenge based on real-world problems to assess collaboration skills

• Meet the leadership team

• Discussion with the CEO