Position Details
Position Information
| Recruitment/Posting Title |
Senior Scientist Research Computing - Data Scientist (Biomedical and Clinical Informatics) |
| Job Category |
Staff & Executive - Information Technology |
| Department |
Office of Advanced Research Computing |
| Overview |
As part of a larger team of research scientists, the incumbent will support the Rutgers University biomedical research community, as well as other research disciplines, in their research computing and data related research. In partnership with the research community and other biomedical and clinical informatics specialists, the successful candidate will manage and analyze data being created in molecular and cellular biology, genomics and biomedicine through the use of existing data science and machine learning tools as well as engineer new toolsets that include models, algorithms, and software developed in-house. Reporting to the Director of Research Support, under the Associate Vice President for Advanced Research Computing, the Senior Scientist engages in local outreach on the Rutgers campuses (Rutgers Biomedical and Health Sciences, New Brunswick, Newark and Camden) to identify potential new users of research computing and data resources. The incumbent works closely with faculty, post-doctoral associates, students, and research staff to understand their research to allow for the customization of workflows, training, and support, and has an opportunity to grow a biomedical and clinical informatics team based on demand for biomedical and clinical informatics services. |
| Posting Summary |
Rutgers, the State University of New Jersey is seeking a Senior Scientist (Biomedical and Clinical Informatics) - Data Scientist
for the Office of Advanced Research Computing (
OARC).
Among the key duties of this position are the following:
- Participate in development of new biomedical and clinical informatics research and support model, potentially leading to creation of a core facility and/or center of excellence.
- Lead and contribute to the design and implementation of experiments in clinical research, collaborating with multidisciplinary teams to plan data acquisition strategies.
- Provide advanced computing and data (biomedical and clinical informatics) support Rutgers faculty and students, but also to the broader community, in their computational research by assisting with conceptual and practical realization of the research goals using local, regional, and/or national advanced computational resources.
- Utilize analytical models and advanced statistical methods to analyze complex clinical datasets, deriving meaningful insights and identifying patterns or correlations. Develop and implement data visualization techniques to effectively communicate findings and facilitate understanding among stakeholders.
- Gain knowledge of other biomedical and clinical informatics activities and support within Rutgers University and facilitate their involvement in research projects that may require their area of specialty.
- Provide education, outreach and training to the university community. Develop and coordinate instructor-based training focused on advanced computing.
- Participate in professional development activities (e.g., training, conferences, etc.), advance personal knowledge in computational science, and develop individual research projects. Present at national meetings.
- Develop and expand internal and external partnerships, including industry, to promote advanced computing related collaborations, positioning Rutgers University as a leader in research and technologies.
- Leads large scale data processing and computational pipeline/tool development in assigned areas, including mentoring of new scientists, graduate students and other technical staff.
- Take a leading role in the selection and optimization of research infrastructure, ensuring it meets the needs of clinical research data analysis and storage, including computing systems, software, data transfer nodes, software defined networking, and compliant protected environments for medical research that requires access to PHI, EMR, or other forms of sensitive data (HIPAA, FISMA, NIST 800-171).
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| Position Status |
Full Time |
| Hours Per Week |
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| Daily Work Shift |
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| Work Arrangement |
Consistent with the current application of Rutgers Policy 60.3.22, this position may be eligible for a hybrid work arrangement. The flexible work arrangements outlined in Rutgers Policy 60.3.22 are part of a pilot program that is effective September 1, 2022 through August 31, 2024. Therefore, there is no guarantee that this flexible work arrangement will continue beyond that date. Flexible work arrangements are not permanent, are subject to change or cancellation and contingent on the employee receiving approval in the FlexWork@RU Application System. Additional information may be found at
https://futureofwork.rutgers.edu. |
| FLSA |
Exempt |
| Grade |
35S |
| Position Salary |
|
| Annual Minimum Salary |
109283.00 |
| Annual Mid Range Salary |
132134.00 |
| Annual Maximum Salary |
157610.00 |
| Standard Hours |
37.50 |
| Union Description |
HPAE 5094 |
| Payroll Designation |
PeopleSoft |
| Benefits |
Rutgers offers a comprehensive benefit program to eligible employees. For details, please go to
http://uhr.rutgers.edu/benefits/benefits-overview.
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| Seniority Unit |
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| Terms of Appointment |
Staff - 12 month |
| Position Pension Eligibility |
ABP |
Qualifications
| Minimum Education and Experience |
- Master's degree required.
- Equivalent education, experience and/or training may be substituted for the degree requirements.
- A minimum of six (6) years experience supporting computationally intensive and/or data intensive research projects or equivalent work.
|
| Certifications/Licenses |
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| Required Knowledge, Skills, and Abilities |
- Strong verbal and written communication skills.
- Enjoy working in a dynamic and flexible team environment and have a positive attitude.
- Able to work with minimal supervision and demonstrate a history of self-motivation.
- Proficiency in statistical methodologies, machine learning techniques, and data visualization tools for analyzing clinical datasets.
- Strong understanding of research infrastructure needs in the context of clinical data warehouses, with the ability to make informed decisions on infrastructure selection and optimization.
- Demonstrate an appreciation for a wide range of computer and data-intensive research and be experienced in at least one of the STEM (Science, Technology, Engineering, or Mathematics) areas.
- Proficient in at least one programming language, preferably Python or R, and work in a Unix-like system.
- Demonstrate deep knowledge of statistical methods and will demonstrate practical knowledge of machine learning model building and deployment.
- Will have produced compelling visualizations telling stories with data.
- Knowledgeable of research processes and language in biological or medical fields and be able to effectively communicate and support researchers in these domains with technological and methodological expertise.
|
| Preferred Qualifications |
- A Ph.D. in a related field.
- Knowledge of the EPIC electronic medical records system and the EPIC Cognitive Computing Platform (ECCP) as well as the OMOP common data model.
- Understanding of how advanced research computing technologies are used to enable scientific discovery.
- Experience applying advanced software tools and computing technologies in a dynamic and diverse research setting.
- Knowledge of regulatory requirements and ethical considerations related to handling clinical data (e.g., HIPAA).
- Demonstrated ability to lead and manage research projects involving complex clinical datasets, from experiment design to data analysis and interpretation.
- Understanding user requirements and translating those requirements into functional and dependable solutions, working with scientific programming languages and troubleshooting skills.
- Knowledge and experience with deep learning frameworks like Tensorflow or PyTorch.
- Experience with statistical tools like SAS, Stata, and SPSS.
- Knowledge of HPC systems.
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| Equipment Utilized |
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| Physical Demands and Work Environment |
- Standing, sitting, walking, talking or hearing.
- Visual acuity to perform activities such as: viewing a computer terminal, reading, analyzing written information/data, etc.
- Office environment. Moderate Noise.
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| Special Conditions |
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Posting Details
| Posting Number |
24ST0885 |
| Posting Open Date |
04/17/2024 |
| Special Instructions to Applicants |
|
| Regional Campus |
Rutgers Biomedical and Health Sciences (RBHS) |
| Home Location Campus |
Piscataway (RBHS) |
| City |
Piscataway |
| State |
NJ |
| Location Details |
Busch Campus, CoRE Building |
Pre-employment Screenings
All offers of employment are contingent upon successful completion of all pre-employment screenings. Immunization Requirements
Under Policy 100.3.1 Immunization Policy for Covered Individuals, if employment will commence during Flu Season, Rutgers University may require certain prospective employees to provide proof that they are vaccinated against Seasonal Influenza for the current Flu Season, unless the University has granted the individual a medical or religious exemption. Additional infection control and safety policies may apply. Prospective employees should speak with their hiring manager to determine which policies apply to the role or position for which they are applying. Failure to provide proof of vaccination for any required vaccines or obtain a medical or religious exemption from the University will result in rescission of a candidate's offer of employment or disciplinary action up to and including termination. Affirmative Action/Equal Employment Opportunity Statement
It is university policy to provide equal employment opportunity to all its employees and applicants for employment regardless of their race, creed, color, national origin, age, ancestry, nationality, marital or domestic partnership or civil union status, sex, pregnancy, gender identity or expression, disability status, liability for military service, protected veteran status, affectional or sexual orientation, atypical cellular or blood trait, genetic information (including the refusal to submit to genetic testing), or any other category protected by law. As an institution, we value diversity of background and opinion, and prohibit discrimination or harassment on the basis of any legally protected class in the areas of hiring, recruitment, promotion, transfer, demotion, training, compensation, pay, fringe benefits, layoff, termination or any other terms and conditions of employment. For additional information please see the Non-Discrimination Statement at the following web address: http://uhr.rutgers.edu/non-discrimination-statement |
Rutgers University
Nov 22, 2024