The Position

Earli Inc. is currently seeking a top caliber Senior Scientist, Bio AI to join our Synthetic Bioengineering team.

Your Primary Responsibilities

• Leverage cutting-edge ML, bioinformatics, and high-throughput assay data to design cancer-specific synthetic promoters and novel genetic medicines that will directly impact Earli’s clinical pipeline.
• Train generative AI models for designing genetic medicines by leveraging Earli’s proprietary Massively Parallel Reporter Assay (MPRA) data as well as external data sets
• Contribute to wet lab experimental design and data evaluation to benchmark AI model performance against ground truth wet lab data and create a rapid iteration loop
• Perform routine computational analyses to analyze MPRA and other large experimental datasets using existing packages as well as bespoke analysis where needed. Provide accessible interfaces (e.g. Shiny apps) for routine data analysis (e.g. RNAseq profiling) for team members
• Perform routine bioinformatic analyses on multi-modal omics data (RNAseq and scRNA-seq, ATAC-seq, proteomics, phospho-proteomics etc.) using individual as well as coherent multi-omic ML-based pipelines to identify key dysregulated targets and pathways in selected cancer indications
• Routinely deploy code and execute on Earli’s infrastructure hosted by Cloud Service Providers (e.g. GCP) with appropriate engineering adaptations as needed. Help develop and work within budgets for GPU usage/compute

Your Required Experience, Knowledge and Skill

• Master’s or PhD degree in a relevant field (bioengineering, computer science, data science, etc.) with a minimum of 3 years of hands-on experience using AI/ML applied to genomic/bioinformatic data using state-of-the-art GenAI models
• Deep, direct expertise (preferably with high-quality publications) in developing novel GenAI models trained on massive biological data. Hands-on expertise in model training, fine-tuning, and in silico evaluation is a pre-requisite for this role.
• An expert level of competence in data analysis on large and complex empirical data, such as MPRA data, multi-modal omics data, etc.
• Familiarity with and prior experience collaborating with wet lab scientists to generate and curate high-throughput screening data on large libraries of DNA or RNA sequences
• Proficiency in routine bioinformatic analyses such as differential gene expression, ATAC-seq and RNA-seq analysis, etc.
• Expert level coding skills in Python and R
• Basic knowledge of fundamental cancer biology is required. Deep expertise in cancer -omics, biomarkers, targets and pathways is preferred
• Excellent verbal and written communication as well as interpersonal skills are required
• Able to multi-task, manage multiple projects simultaneously and work effectively within a team
• Ability to think independently and fully integrate into a high achieving team environment

The base salary for this position is $205,000-$235,000 per year.