About The Position
Information Science Professionals utilize applied or computational mathematical analyses for a wide array of different applications and to solve complex problems. Experiments may include text interpretation, coding, ground theory methodology for the analysis of certain data, and quantum state analyses. Information Science Professionals may also perform duties in labs that use primarily electronic equipment. This Information Science Professional will be operating as a Machine Learning (ML) Engineer to help the Department of Radiology create artificial intelligence analysis of medical images. Working under the Principal Investigator (PI), Dr. Bennett Chin. The ML Engineer will be assisting with the creation of machine learning models and retraining systems using radiology data. To do this job successfully, the candidate will need exceptional skills in mathematics and programming; knowledge of data science and experience with software engineering is desired. The ultimate goal of this position will be to shape and build efficient deep learning applications. This is a part-time, 0.2 FTE, position with an option to work remotely.
Requirements
- Bachelor’s degree in Bioinformatics, Biostatistics, Computational Biology, Data Science, Computer Science, Mathematics, or related field.
- A combination of education and related technical/paraprofessional experience may be substituted for the bachelor’s degree on a year for year basis.
- One (1) year professional data management and bioinformatic analyses experience (Intermediate Level)
- Two (2) years professional data management and bioinformatic analyses experience (Senior Level)
- Minimum three (3) years professional data management and bioinformatic analyses experience (Principal Level)
- Applicants must meet minimum qualifications at the time of hire.
- Strong to expert ability to analyze and solve complex problems and apply quantitative analytical approaches, depending on level.
- Demonstrated fluency in one or more programming languages (e.g., R, Python, Perl, Java, C++) and willingness to learn new programming languages as necessary.
- Understanding of data structures, data modeling and software architecture.
- Deep knowledge of math, probability, statistics and algorithms.
- Familiarity with machine learning frameworks (like Keras or PyTorch) and libraries (like scikit-learn).
- Ability to communicate effectively, both in writing and orally.
- Ability to establish and maintain effective working relationships with employees at all levels throughout the institution
Nice To Haves
- Master’s degree in Bioinformatics, Biostatistics, Computational Biology, Data Science, Computer Science, Mathematics, or related field.
- One (1) to four (4) years of experience analyzing data using high-performance computing.
Responsibilities
- Collaborate with and support Principal Investigators (PI) and other stakeholders in the area of bioinformatics and data analysis
- Perform scientifically rigorous data management and bioinformatic analyses.
- Run machine learning tests and experiments.
- Computer System software maintenance and security.
- Assist with selection of appropriate datasets and data representation methods.
- Perform evaluation and analysis of test results.
- Train and retrain systems when necessary.
- Develop and disseminate a variety of tools designed to access relevant clinical and sample data
- Develop machine learning applications according to requirements.
- Research and implement appropriate ML algorithms and tools.
- Develop and implement complex analyses pipelines, programming, and data visualization techniques
- Extend existing ML libraries and frameworks.
- Creatively and effectively integrate data from multiple sources to accelerate discoveries
- Study and transform data science prototypes.
- Assist with the design and development of major bioinformatics-related programming projects
- Write custom scripts to access databases and analyze data
- Keep abreast of developments in the field.
- Independently and creatively identify bioinformatic and data management solutions.
- Assist Team Leads, Supervisors and/or management with creation and implementation of processes and procedures and quality improvement initiatives.
- Assist and train junior team members.
- Assist with developing or develop protocol-specific systems and documents including process flows, training manuals, and Standard Operating Procedures (SOPs). Maintains subject level documentation and prepares documents, equipment and/or supplies.
- Assist with identifying issues related to operational efficiency and shares results with leadership.
- Provide the biostatistical/data science expertise and leadership in study design, study oversight, data management, data analysis and manuscript preparation to assist all levels of biomedical investigators and clinicians on new research activities across a wide range of disciplines.
- Serve as a resource to PIs and other stakeholders.
- Act as a Subject Matter Expert and authority in the area of machine learning.
Benefits
- Medical: Multiple plan options
- Dental: Multiple plan options
- Additional Insurance: Disability, Life, Vision
- Retirement 401(a) Plan: Employer contributes 10%25 of your gross pay
- Paid Time Off: Accruals over the year
- Vacation Days: 22/year (maximum accrual 352 hours)
- Sick Days: 15/year (unlimited maximum accrual)
- Holiday Days: 15/year
- Tuition Benefit: Employees have access to this benefit on all CU campuses
- ECO Pass: Reduced rate RTD Bus and light rail service
- There are many additional perks & programs with the CU Advantage.
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What This Job Offers
Job Type
Part-time
Career Level
Mid Level
