Job Description:
Do you have a passion for analyzing scientific data and broad experience crafting bioinformatics pipelines? Do you think that cancer treatment should be personalized and want to accelerate that reality? Are you looking for a mission driven company where your work will directly impact human lives? Notable Labs seeks a lead bioinformatics engineer to found our data science team. As a technical leader in a quickly growing startup, you will build machine learning tools and data pipelines, advise on software architecture and experimental design, analyze proteomic and cell imaging data, and drive the data strategy foundational to our mission: all cancer is treatable. We're building a translational drug discovery platform to identify treatment options for relapsed and refractory cancer patients -- starting with Acute Myeloid Leukemia and Glioblastoma Brain Cancer -- to address the long tail of cancer treatment. We have a highly automated lab in San Francisco running on our custom software (Python/Django, JavaScript/React, PostgreSQL), and are currently testing relapsed/refractory cancer patients as well as samples from a variety of biopharma partnerships. What you’ll do:
Additional Info:
Notable Labs Overview: Changing the way cancer is treated is our mission, which starts with putting patients first. We’ve developed a high throughput robotic lab platform that uses a patient’s live tumor cells -- in a microenvironment that mimics the human body -- to predict the safest and most effective cancer treatments. We screen thousands of FDA-approved drug combinations against the patient's own cancer cells to identify drug combinations that can be immediately prescribed by their doctor without a clinical trial. The end result of our process is a report which prioritizes therapeutic options for the patient based on how well the treatment targets their cancer cells relative to healthy cells. Our platform is also used by a number of biotech and pharmaceutical partners to test the biological impact of novel drug combinations in a physiologically relevant environment, which improves and accelerates the drug development process. We harness the power of data science, lab automation, and software engineering to personalize cancer treatment and enhance drug development. Our investors include Founders Fund, First Round Capital, Y Combinator, several prominent angels and seed-stage funds, and Accelerate Brain Cancer Cure, a venture philanthropy firm founded by Steve Case. We have offices and a laboratory in San Francisco’s SoMa district. At Notable Labs we value diversity and are an equal opportunity employer. We do not discriminate on the basis of race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status.[Click Here to Access the Original Job Post]
Do you have a passion for analyzing scientific data and broad experience crafting bioinformatics pipelines? Do you think that cancer treatment should be personalized and want to accelerate that reality? Are you looking for a mission driven company where your work will directly impact human lives? Notable Labs seeks a lead bioinformatics engineer to found our data science team. As a technical leader in a quickly growing startup, you will build machine learning tools and data pipelines, advise on software architecture and experimental design, analyze proteomic and cell imaging data, and drive the data strategy foundational to our mission: all cancer is treatable. We're building a translational drug discovery platform to identify treatment options for relapsed and refractory cancer patients -- starting with Acute Myeloid Leukemia and Glioblastoma Brain Cancer -- to address the long tail of cancer treatment. We have a highly automated lab in San Francisco running on our custom software (Python/Django, JavaScript/React, PostgreSQL), and are currently testing relapsed/refractory cancer patients as well as samples from a variety of biopharma partnerships. What you’ll do:
- Build and design machine learning pipelines for the automated analysis of flow cytometry and cell imaging data
- Develop a statistical process control framework for flow cytometry validation and laboratory quality control
- Analyze production and research flow cytometry, cell imaging, and drug response data to report to clinicians and biopharma partners
- Design algorithms to optimize our combinatorial drug search and inform drug development hypotheses
- Collaborate with the science team on the design and analysis of research experiments
- Work in a dynamic interdisciplinary environment on multi-functional project teams of: software engineers, automation engineers, data scientists, bioengineers, computational biologists, process engineers, clinical and R&D scientists, etc.
- Regularly present your results and analysis at group and individual meetings as well as externally through conferences and publications
- Use a modern data stack to analyze data and develop methods: Jupyter, Pandas, SciPy, NumPy, SciKits, Python, Docker, R, etc.
- Love wrangling complex biological datasets to derive innovative insights and are passionate about personalizing the treatment of cancer
- Deep knowledge of statistics, machine learning, and data analysis as well as a broad working knowledge of common bioinformatics tools/methods
- PhD in bioinformatics, computational biology, {bio}statistics, or equivalent experience and training
- 3+ years of postgraduate experience working in a production environment with large data sets using Python/Jupyter or R
- Have contributed significant publication quality work that is demonstrated through your publication record, personal web page, GitHub account, or prior experience
- Solid programming skills and proficiency with Unix, Git, and other command line tools
- Familiar with machine vision and image analysis algorithms and research
- Flow cytometry or cell imaging data analysis experience is a plus
Requeriments :
Skills :
Areas :
Additional Info:
Notable Labs Overview: Changing the way cancer is treated is our mission, which starts with putting patients first. We’ve developed a high throughput robotic lab platform that uses a patient’s live tumor cells -- in a microenvironment that mimics the human body -- to predict the safest and most effective cancer treatments. We screen thousands of FDA-approved drug combinations against the patient's own cancer cells to identify drug combinations that can be immediately prescribed by their doctor without a clinical trial. The end result of our process is a report which prioritizes therapeutic options for the patient based on how well the treatment targets their cancer cells relative to healthy cells. Our platform is also used by a number of biotech and pharmaceutical partners to test the biological impact of novel drug combinations in a physiologically relevant environment, which improves and accelerates the drug development process. We harness the power of data science, lab automation, and software engineering to personalize cancer treatment and enhance drug development. Our investors include Founders Fund, First Round Capital, Y Combinator, several prominent angels and seed-stage funds, and Accelerate Brain Cancer Cure, a venture philanthropy firm founded by Steve Case. We have offices and a laboratory in San Francisco’s SoMa district. At Notable Labs we value diversity and are an equal opportunity employer. We do not discriminate on the basis of race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status.[Click Here to Access the Original Job Post]