Headquartered in San Diego, California, we are an early-stage, well-funded Techbio company specializing in innovative drug discovery solutions. Our proprietary 3D organ-on-a-chip platform, Curiochips, offers significant advantages in accurately recapitulating both normal and disease states of the human body. This capability has been validated through multiple ongoing collaborations with hospitals, government institutions, and major pharmaceutical companies.
Our Mission
At Qureator Inc., we are committed to revolutionizing the drug discovery process. Our mission is driven by the Qureator platform's unparalleled ability to replicate complex disease phenotypes, surpassing the limitations of traditional preclinical models. By bridging the gap between laboratory research and real patient outcomes, we aim to accelerate the development of treatments for a wide range of conditions, from cancers to rare diseases.
Our Approach
We tackle diseases that lack clear in vitro models, setting new standards in preclinical research. Our comprehensive approach to phenotypic analysis includes detailed disease tissue phenotyping, which is essential for observing complex drug responses. This effort is crucial for advancing treatments informed by the complexities of human biology.
Position: Director/Associate Director of Data Science
We are looking for a highly collaborative and innovative individual to join us as a Director of Data Science. This role will be responsible for leading and building the data science team and infrastructure in our San Diego office (headquarters). This is a key function we are building to drive the understanding of differences between our models and human disease. We are seeking a dynamic and visionary director to lead this transformative journey. The team will lead our exploration in developing novel data visualization and machine learning methods to define disease states in our tissue models.
As the Director of Data Science at Qureator, you will lead a journey of transformation. You are the architect who will build and steer a data science team poised to harness the potential of Qureator’s platform technology. Your leadership will refine computational models to be aligned with real-world disease states, furthering our mission to offer more predictive and relevant models that can accelerate the development of new therapies.This role demands a blend of leadership, technical expertise and passion for innovation, offering unparalleled opportunity to impact the field of health care and biotechnology.
The candidate will work within a cross-functional team of engineers, biologists, and data scientists at our San Diego and Seoul office. The successful candidate will be required to learn and communicate with the cross-functional team to organize and analyze high dimensional patient and 3D organ on chip data to guide the decisions.
Key responsibilities will include but are not limited to:
Team building and leadership:
Search and recruit high potential individuals to build a world class data-science team.
Explore possible directions for understanding and comparing multi-cell-type tissue responses.
Lead the development of data analysis pipeline to support compound profiling with Qureator’s platform.
Keep the team updated with novel machine leaning technologies and platforms. Identify opportunities for innovation and improvement.
Establish and mentor core skills for the data-science team, fostering a culture of continuous learning and professional development.
Communicate with the biology and engineering team to keep goals and timelines aligned.
Work in a fast-paced, multi-tasking environment with the biology and engineer team to support company objectives.
Preferred Qualification
Master or PhD in computer science, mathematics, computational biology, or comparable areas with more than 5 years of industrial experience
Experience with leading or building data-science or machine learning functions
Experience with cloud computing platforms (e.g., AWS, Azure) and big data technologies.
Proven experience in developing AI/ML models for image analysis, preferably with 3D imaging data.
Experience with machine learning frameworks and libraries (e.g., TensorFlow, PyTorch, scikit-learn).
Publications in top-tier conferences or journals related to AI/ML.
Employment type
Full-time
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