Founding Scientist Synthetic Genomics - Exonic

Key Responsibilities

• Design and implement unsupervised machine learning pipelines to predict functional genomic elements and guide synthetic genome construction.
• Integrate high‑throughput sequencing data with CRISPR‑based perturbation experiments to refine predictive models.
• Collaborate with computational biologists and wet‑lab scientists to validate model outputs and iterate on design strategies.
• Publish findings in peer‑reviewed journals and present at scientific conferences.
• Mentor junior researchers and contribute to the growth of the synthetic genomics research group.

Requirements

• PhD in Computational Biology, Genomics, or related field with strong machine learning background.
• Proven experience in unsupervised learning, deep learning, or generative models applied to biological data.
• Hands‑on expertise with CRISPR/Cas9 genome editing and high‑throughput sequencing analysis.
• Strong programming skills in Python and familiarity with bioinformatics tools (e.g., Biopython, GATK).
• Excellent communication skills and ability to translate complex data insights into actionable biological strategies.