
GeneEase is pioneering advanced gene therapies to target subclinical conditions before they progress. The company focuses on developing novel approaches to gene therapy, aiming to bridge the gap in genetic medicine by providing comprehensive phenotypic data collection. Their innovative solutions are designed to enhance decision-making in genetics labs, making them a key player in the healthcare sector.

GeneEase is pioneering advanced gene therapies to target subclinical conditions before they progress. The company focuses on developing novel approaches to gene therapy, aiming to bridge the gap in genetic medicine by providing comprehensive phenotypic data collection. Their innovative solutions are designed to enhance decision-making in genetics labs, making them a key player in the healthcare sector.
About Us
GeneEase discovers novel gene therapies for subclinical conditions overlooked by traditional medicine - genetic disorders affecting millions (alcohol intolerance, lactose intolerance, mild autoimmunity) where existing treatments are inadequate or nonexistent.
We use computational biology to identify promising therapeutic targets, design gene therapy approaches (AAV, base editing, other modalities), validate mechanisms in silico, and partner with wet labs for experimental confirmation. We file patents and license IP to gene therapy companies for clinical development.
Role Overview
Lead computational gene therapy : design therapeutics that can be manufactured, delivered, and clinically translated - not just theoretically promising targets.
You'll evaluate targets, design vectors with practical constraints in mind (manufacturability, delivery, immunogenicity), validate in silico, and coordinate academic partnerships for experimental validation.
80% computational work, 20% wet lab coordination. You design experiments—partners execute them. Critical: You must understand what makes gene therapies succeed or fail in practice, not just in silico.
Key Responsibilities
Therapeutic Design with Translational Focus (40%)
In Silico Validation (40%)
Lab Partnerships (15%)
Communication & IP (5%)
Requirements
Education: PhD in Computational Biology, Bioinformatics, Bioengineering, Systems Biology, or related fields (or MS with 3-5 years experience)
Wet Lab Experience: 1-3 years hands-on experience (cloning, cell culture, transfection, assays). Gene therapy experience strongly preferred (AAV/lentivirus production, transduction, functional validation, titer quantification).
Gene Therapy Technical: Vector design (AAV serotypes, promoter selection, cargo optimization, CRISPR guide RNAs), tools (Benchling, SnapGene)
Gene Therapy Development Mindset:
Computational: Protein modeling (AlphaFold, Rosetta), molecular dynamics (GROMACS/AMBER), pathway analysis (STRING, Reactome), PBPK modeling
Programming: Python (BioPython, pandas, PyTorch), R (Bioconductor), SQL, Git, Linux/HPC
Nice-to-Haves
Essential Traits
Why Join Us
How to Apply
Please submit your application at: https://jouster.notion.site/2bd5c65e6f0d817eb513f910f205b4ab
We look forward to hearing from you!