Job Description
Job Title: Molecular Biologist
Job Type: Contract
Location: Remote
Job Summary:
Join our customer's team as a Molecular Biologist, specializing in CRISPR and gene editing, to advance cutting-edge projects and contribute to AI training initiatives. You will leverage your expertise to design, execute, and optimize molecular biology workflows, supporting innovative research and development efforts.
Key Responsibilities:
- Lead the design, optimization, and execution of CRISPR-based gene editing experiments.
- Develop and implement cloning strategies to generate novel constructs and cell lines.
- Perform genotyping, PCR-based assays, and sequence analyses to validate genetic modifications.
- Design synthetic DNA/RNA sequences and contribute to screening logic for high-throughput workflows.
- Collaborate with interdisciplinary teams to translate experimental data into structured formats for AI model training.
- Apply molecular biology techniques to study and characterize molecules, organelles, and cellular organization.
- Document experimental procedures and results with exceptional clarity and precision, supporting reproducibility and knowledge transfer.
Required Skills and Qualifications:
- Expertise in CRISPR technology and gene editing workflows.
- Extensive hands-on experience with cloning, genotyping, and PCR-based assays.
- Strong background in sequence design and molecular screening strategies.
- Excellent written and verbal communication skills, with keen attention to scientific detail.
- Ability to research and analyze molecular and organelle functions within cells.
- Demonstrated commitment to data accuracy, workflow optimization, and experimental rigor.
- Self-driven and collaborative, with a track record of contributing to high-impact research projects.
- Bachelor’s degree or higher in Molecular Biology, Biology, or a related field.
Preferred Qualifications:
- Experience with the development or evaluation of rubrics, especially for AI and data annotation workflows.
- Familiarity with designing datasets or protocols for AI training and human review processes.
- Previous collaboration with interdisciplinary or remote teams on data-driven biology projects.