(ID: 2025-0404)
Axle is a bioscience and information technology company that offers advancements in translational research, biomedical informatics, and data science applications to research centers and healthcare organizations nationally and abroad. With experts in biomedical science, software engineering, and program management, we focus on developing and applying research tools and techniques to empower decision-making and accelerate research discoveries. We work with some of the top research organizations and facilities in the country including multiple institutes at the National Institutes of Health (NIH).
Overview:
The Standardized Organoid Model Center is an NIH-funded initiative dedicated to advancing organoid research through the development of validated, reproducible, and well-characterized organoid models. The center brings together interdisciplinary teams of researchers to establish standardized protocols, develop quality control measures, and create resources that will benefit the broader organoid research community.
Responsibilities:
- The successful candidate will design and implement machine learning algorithms that integrate diverse omics datasets including genomics, transcriptomics, proteomics, and metabolomics data to create comprehensive organoid characterization profiles.
- They will develop predictive models that assess organoid quality and functionality based on molecular signatures and identify biomarkers that correlate with successful organoid development.
- The role involves creating computational tools for comparing organoid characteristics across different protocols and laboratories to support standardization efforts.
- Collaboration with experimental teams to validate computational predictions and translate findings into actionable protocol improvements will be essential.
Required Qualifications:
- Candidates must hold a PhD in computational biology, bioinformatics, computer science, or a related quantitative field with demonstrated experience applying AI/ML methods to biological systems.
- Strong programming skills in Python and R are required, along with experience with machine learning frameworks and statistical analysis packages.
- Knowledge of multi-omics data integration techniques and experience with biological pathway analysis are necessary.
- Familiarity with cloud computing platforms and high-performance computing environments is required.
Preferred Qualifications:
- Previous experience working with organoid datasets or tissue engineering applications is highly desirable.
- Experience with deep learning approaches for biological data, knowledge of systems biology principles, and familiarity with network analysis methods will be considered valuable assets.
- Experience with collaborative research projects and manuscript preparation is preferred.
Disclaimer: The above description is meant to illustrate the general nature of work and level of effort being performed by individuals assigned to this position or job description. This is not restricted as a complete list of all skills, responsibilities, duties, and/or assignments required. Individuals may be required to perform duties outside of their position, job description or responsibilities as needed.
The diversity of Axle's employees is a tremendous asset. We are firmly committed to providing equal opportunity in all aspects of employment and will not tolerate any illegal discrimination or harassment based on age, race, gender, religion, national origin, disability, marital status, covered veteran status, sexual orientation, status with respect to public assistance, and other characteristics protected under state, federal, or local law and to deter those who aid, abet, or induce discrimination or coerce others to discriminate.
Accessibility: If you need an accommodation as part of the employment process please contact: careers@axleinfo.com
This role has a market-competitive salary with an anticipated base compensation range listed below. Actual salaries will vary depending on a candidate's experience, qualifications, skills, and location.
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