Full-Time Computational Bioengineer - Gene Therapy Vector Design

About Us: GeneEase discovers novel gene therapies for subclinical conditions. We use computational biology to identify therapeutic targets and design gene therapy approaches. We partner with wet labs for experimental confirmation and license IP to gene therapy companies.

Role Overview: Lead computational gene therapy development, focusing on practical constraints for manufacturability, delivery, and clinical translation. You'll evaluate targets, design vectors, validate in silico, and coordinate academic partnerships.
80% computational work, 20% wet lab coordination. You design experiments—partners execute them.
Critical: Understand what makes gene therapies succeed or fail in practice.

Key Responsibilities:

• Therapeutic Design (40%): Evaluate genetic targets, design gene therapy approaches considering manufacturability, deliverability, and regulatory feasibility. Optimize constructs.
• In Silico Validation (40%): Protein modeling (AlphaFold, GROMACS), safety assessment (biodistribution, immunogenicity), and translational risk assessment. Generate validation reports.
• Lab Partnerships (15%): Identify labs, design experimental protocols, analyze results, troubleshoot failures, and iterate designs.
• Communication & IP (5%): Draft manuscripts, patent applications, and pharma partner dossiers.

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.
• Gene Therapy Technical: Vector design (AAV serotypes, promoter selection, cargo optimization, CRISPR guide RNAs), tools (Benchling, SnapGene)
• Gene Therapy Development Mindset: Understand factors of vector success/failure in practice. Consider manufacturability, deliverability, and immunogenicity.
• 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:

• Gene therapy industry experience.
• IND-enabling study experience.
• AAV manufacturing knowledge.
• Academic/CRO partnership management.
• Regulatory awareness.

Essential Traits:

• Autonomous problem-solver with mechanistic thinking.
• Bridges computational predictions with biological reality.
• Builds tools, not just uses them.
• Communicates complex work to non-technical stakeholders.

Why Join Us: Shape the foundation of a product that bridges biology and computation. Collaborate with a global, interdisciplinary team. Flexible, remote-first engagement. Opportunity to see your expertise directly influence product development.

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