Research Data Analyst 1

Details

Posted: 07-Apr-24

Location: Stanford, California

Type: Full-time

Salary: Open

Categories:

Staff/Administrative

Internal Number: 102819

The Stanford University Center for Precision Mental Health and Wellness is seeking a motivated and well-trained research data analyst to manage and analyze high dimensional neuroimaging and behavioral datasets acquired in precision mental health studies. Especially sought are candidates with expertise in functional imaging data analysis in human subjects studies.

The position will be based within Center's Personalized and Translational Neuroscience lab. Studies in the lab use brain imaging approaches to improve our understanding and treatment of mental health conditions such as depression and anxiety. These studies are funded through the NIH and philanthropy.

The Research Data Analyst (RDA) will be tasked with managing incoming data, implementing data quality controls, visualizing data and generating and implementing analysis models for neuroimaging and behavioral data and their integration. Data are acquired at multiple time points, including pre- and post-treatment. The RDA will also be responsible for sharing data through NIH data coordinating centers. The tasks are supported by an existing database and server infrastructure, an large existing datasets.

The RDA will work in close collaboration with an interdisciplinary team. There is a need for flexibility to work across different scripting and software environments and display agility in learning. Members of the Center possess deep domain experience in their chosen fields and an ability to communicate across fields.

The position will be fully in person.

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Interested candidates should include:

A cover letter addressing requirements and why you are motivated to apply to this position and contribute to research in precision mental health and how your education and experience relate to the position as described above.

Resume or CV

At least three references to [email protected] . The position is open until filled. However, because of funding timelines and project milestones, we are seeking to fill this position as soon as possible.

The supervising PI for this position is Dr. Leanne Williams, https://profiles.stanford.edu/leanne-williams .

Learn more about the Lab and Center: http://med.stanford.edu/pmhw . The position will be based within a collaborative team that values cooperation, fairness, efficiency, and conscientiousness.

Specific Tasks include:

• Collect, manage and clean large datasets.

• Employ new and existing tools to interpret, analyze, and visualize multivariate relationships in human subjects data.

• Create databases and reports, develop algorithms and statistical models, and perform statistical analyses appropriate to data and reporting requirements.

• Use system reports and analyses to identify potentially problematic data, make corrections, and determine root cause for data problems from input errors or inadequate field edits, and suggest possible solutions.

• Develop reports, charts, graphs and tables for use by investigators and for publication and presentation.

• Analyze data processes in documentation.

• Collaborate with faculty and research staff on data collection and analysis methods.

• Provide documentation based on audit and reporting criteria to investigators and research staff.

• Communicate with grant agencies in regard to data sharing centers.

* - Other duties may also be assigned

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DESIRED QUALIFICATIONS:

• Familiarity with fMRI data analysis techniques, such as using SPM, Freesurfer

• Experience with complex human subjects data management

• Knowledge of statistical and machine learning techniques for data analysis

• Experience working in research or academic setting

• Familiarity with data visualization tools

EDUCATION & EXPERIENCE (REQUIRED):

• Bachelor's degree or a combination of education and relevant experience. Experience in a quantitative discipline relevant to the domain of the research in the lab, such as psychology, neuroscience, or statistics.

KNOWLEDGE, SKILLS AND ABILITIES (REQUIRED):

• Motivation to contribute to advances in precision mental health

• Proficiency in statistical analysis software (e.g., SPSS, R, Python)

• Experience working with complex datasets

• Substantial experience with MS Office and analytical programs

• Strong writing, problem solving and analytical skills

• Ability to prioritize workload

• Ability to manage multiple projects and deadlines

PHYSICAL REQUIREMENTS*:

• Sitting in place at computer for long periods of time with extensive keyboarding/dexterity.

• Occasionally use a telephone.

• Rarely writing by hand.

• - Consistent with its obligations under the law, the University will provide reasonable accommodation to any employee with a disability who requires accommodation to perform the essential functions of his or her job.

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WORKING CONDITIONS:

• Some work may be performed in a laboratory or field setting.

• The work arrangement for this position will be on-site and will be based on the Stanford main campus.

The expected pay range for this position is $64,480 to $97,000 per annum. Stanford University provides pay ranges representing its good faith estimate of what the university reasonably expects to pay for a position. The pay offered to a selected candidate will be determined based on factors such as (but not limited to) the scope and responsibilities of the position, the qualifications of the selected candidate, departmental budget availability, internal equity, geographic location and external market pay for comparable jobs.

* - Stanford is an equal employment opportunity and affirmative action employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, protected veteran status, or any other characteristic protected by law.

Additional Information

• Schedule: Full-time
• Job Code: 4751
• Employee Status: Regular
• Grade: G
• Requisition ID: 102819
• Work Arrangement : On Site