Earli exists to make cancer a benign experience. Earli does that by turning cancers against themselves: genetically forcing them to reveal themselves early, and then kill themselves – precisely and clearly distinguishable from benign lesions at early stages. Based on original technology from Stanford’s renowned Gambhir lab, Earli designs genetic constructs that are injected intravenously that turn cancer cells against themselves. These programmable synthetic promoter-reporter sequences “flip on” like light switches only in dysregulated cancer cells and turn them into "factories." The cancer is forced to produce either an epitope “docking station” for imaging agents, or a cytokine for immune system activation against the tumor. Thus, Earli’s platform enables immediate diagnosis and treatment of early cancers, rather than long-term observation that can lead to deadly metastatic recurrence.
Earli's synthetic target expression platform has evolved over five years of deep bioengineering. The system can now detect broad ranges of patient mutations, distinguish between malignant and benign lesions, and offer independence from often elusive natural biomarkers.
Who You Are
- You share our same sense of dedication, scientific passion and entrepreneurial spirit
- You work well in a fast-paced and extremely focused startup environment
- You are not only smart, but clever and constantly think outside the box
- You are able to make logical decisions in an instant when there is little time to evaluate
- You are a natural communicator and relationship builder
- You stay calm under high pressure and stress
- You have the ability to multi-task in a serious way, with an extreme attention to detail
- You become a representative of the core DNA of the company through who you are
The Position
Earli Inc. is currently seeking a highly motivated and creative Scientist to join the Synthetic Gene Regulation team.
Your Primary Responsibilities
- Work within the team to design, develop and test combinations of novel promoter, enhancer, and other regulatory elements for the company’s cancer-activated synthetic expression platform
- With support from the computational biology team, leverage computational analysis of cancer multi-omics data and existing literature to identify key dysregulated pathways in selected cancer indications (especially dysregulated transcription factors), and build synthetic promoters to drive gene expression in response to those pathways
- Execute high-throughput screens to optimize synthetic promoters and generate massive datasets on sequence-activity relationships. Working with the data science team, help develop AI/ML models to computationally design and refine promoter activity
- Develop creative strategies to increase the strength and durability of expression from synthetic gene expression constructs by engineering regulatory elements such as 5’ and 3’ UTRs, codon optimization, mRNA structure, etc.
- Execute comprehensive studies using reporter protein assays, qPCR, and various omics methods (e.g. RNA-seq, scRNA-seq and ATAC-seq) to validate the performance of synthetic expression constructs in mammalian cells (including primary cells).
- Document results thoroughly and communicate findings internally and externally through presentations and reports
- Stay current with relevant scientific literature and technologies to improve experimental and computational workflows
Your Required Experience, Knowledge and Skill
- PhD degree in a relevant life sciences discipline (Bioengineering, Synthetic Biology, Molecular Biology, etc.) plus 1-2 years of postdoctoral or equivalent industry experience
- Minimum of 4-6 years of experience in mammalian synthetic biology or gene regulation is required
- Deep, direct expertise (as evidenced by high-quality publications or patents) in developing and validating the performance of gene expression systems by engineering promoters, enhancers, logic circuits, other regulatory elements (e.g. miRNAs, UTRs, etc.) is required
- Basic knowledge of fundamental cancer biology is required. Deep expertise in cancer -omics, biomarkers, targets and pathways is preferred
- High level of proficiency with high-throughput screening strategies (barcoding, automation, etc) for massively parallel evaluation of large synthetic libraries in mammalian cells is preferred
- Expert-level molecular biology skills including complex/large scale cloning, custom NGS library prep and analysis, RT-qPCR, etc. are required
- Good working knowledge of evaluation of gene expression constructs in mammalian cells (including primary cells) and in mouse models is required
- Basic proficiency with computational biology skills such as bulk and single-cell -omics analyses is preferred. Knowledge and direct experience with AI/ML techniques such as building and training models on large datasets is highly desirable
- Excellent verbal communication and 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
If interested in applying, please attach a CV or have a well-developed LinkedIn profile for us to be able to assess your background.
We look forward to hearing from you!