Research fellow - machine learning lab
Greenstonebio
About Greenstone Biosciences Inc ( is a health care company that is dedicated to drug discovery. Using its unique drug discovery pipeline comprised of Machine Learning, Virtual screening of chemical libraries, molecular docking, high throughput multi-omics sequencing, and human derived induced pluripotent stem cell technologies (hiPSCs), Greenstone Biosciences aims to develop novel drug therapeutics to achieve precision medicine and precision health. Greenstone Biosciences is headquartered in the Alexandria Center for Life Science at Stanford Research Park in Palo Alto, CA.
Human iPS cells, stem cells, cardiac cells, experience with handling mice and drug discovery research.
This position will work with an interdisciplinary group (stem cell biologists, chemists, structural biologists, clinical, laboratory operations) to develop drug discovery pipeline.
Your Qualifications: Bachelors, Masters or PhD Degree in the Life Sciences such as Biochemistry, Cell Biology, Developmental Biology, Pharmacology, Pharmaceutical Sciences, Pharmacology or related field.
1-2 years of relevant work experience with PhD or a Bachelors or Masters degree with 5+ years of relevant work experience in drug discovery or translational medicine.
Familiarity with genome editing and functional genomics strategies using CRISPR/Cas9
Experience with qPCR, western blots and other relevant laboratory techniques
Coordinate or carryout genetic engineering of pluripotent stem cells for numerous downstream applications to advance therapeutic programs
Perform characterization experiments, drug screening, make detailed scientific observations, analyze data, interpret and present results and record results
Develop scalable, fully or semi-automated, workflows for the establishment of iPSC-derived cell model platforms in collaboration with the team
Collaborate in the development of sophisticated model systems based on iPSCs differentiated into multiple cell types relevant to the ongoing research activities
$143k - $175k
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