Postdoctoral Research Associate – Radiology Full-time

Postdoctoral Research Fellow In Neuroimaging, Ai, And Statistical Genomics

We are considering the applications of a postdoctoral research fellow in neuroimaging, artificial intelligence (AI), and statistical genomics. This exciting career-building position is within the Department of Radiology, which currently ranks the third-highest NIH-funded among the Radiology Departments in the US. The position will work under Dr. Ganesh Chand, Assistant Professor of Radiology, within WashU Medicine in St. Louis, a top-ranked medical school in research. The candidate will work on identifying multimodal biomarkers, specifically leveraging magnetic resonance imaging (MRI), positron emission tomography (PET), functional MRI (fMRI), electroencephalography (EEG), behavior, genetics, and proteomics using advanced quantitative modeling techniques and artificial intelligence methodologies in brain diseases. The candidate will work on developing advanced new algorithms, testing and validation, and applications in these data modalities. The candidate will have the opportunity to work on “big data” studies in health and diseases, including Alzheimer's disease and others such as schizophrenia, psychosis, autism, etc. We collaborate with major research universities worldwide as well as with neuro-related industries.

Primary duties & responsibilities include:

• Assists with grant preparation and reporting.
• Prepares and submits papers on research.
• Assists in the design of research experiments.
• Evaluates research findings and assists in the reporting of the results.
• Conscientious discharge of research responsibilities.
• Maintains conformity with ethical standards in research.
• Maintains compliance with good laboratory practice including the maintenance of adequate research records.
• Performs quality checks of brain PET/MRI cognitive, clinical, genetic, and proteomic data and manages them in the data repository and computer servers.
• Runs existing PET/MR brain image processing pipelines on the computer servers, produces the results, and communicates with the group members.
• Writes computer codes for the above data modalities under the guidance of the team leader.
• Engages in the development and testing/validation of new quantitative AI algorithms and their applications to PET, MRI, EEG, behavioral, clinical, genetic, and proteomic data.
• Prepares documentation of existing and newly developed brain image analysis pipelines, algorithms, and quantitative methods.
• Assists the team leader in generating preliminary results for grant funding proposals and manuscript preparation.
• Publishes research findings in reputable scientific journals.
• Engages in open and timely discussion with their mentor regarding possession or distribution of material, reagents, or records belonging to their laboratory and any proposed disclosure of findings or techniques privately or in publications.
• Collegial conduct towards co-trainees, staff members and members of the research group.
• Adherence to all applicable University policies, procedures and regulations. All data, research records and materials and other intellectual property generated in University laboratories remain the property of the University.

Working conditions include:

This position works in a laboratory environment with potential exposure to biological and chemical hazards. The individual must be physically able to wear protective equipment and to provide standard care to research animals.

Salary range is base pay commensurate with experience.

The above statements are intended to describe the general nature and level of work performed by people assigned to this classification. They are not intended to be construed as an exhaustive list of all job duties performed by the personnel so classified. Management reserves the right to revise or amend duties at any time.

Required qualifications include:

Education: Ph.D., M.D. or equivalent terminal or doctoral degree.

Certifications/Professional Licenses: None required.

Work Experience: None required.

Skills: Not applicable.

Driver's License: Not required.

Preferred qualifications include:

• Experience with multi-omics data analysis.
• Experience with neuroimaging-behavior and/or neuroimaging-genetics analysis.
• Familiar with emerging AI techniques, neuroimaging methods, and statistical genetics research.

For frequently asked questions about the application process, please refer to our External Applicant FAQ.

If you are unable to use our online application system and would like an accommodation, please email CandidateQuestions@wustl.edu or call the dedicated accommodation inquiry number at 314-935-1149 and leave a voicemail with the nature of your request.

All qualified individuals must be able to perform the essential functions of the position satisfactorily and, if requested, reasonable accommodations will be made to enable employees with disabilities to perform the essential functions of their job, absent undue hardship.

All external candidates receiving an offer for employment will be required to submit to pre-employment screening for this position. The screenings will include criminal background check and, as applicable for the position, other background checks, drug screen, an employment and education or licensure/certification verification, physical examination, certain vaccinations and/or governmental registry checks. All offers are contingent upon successful completion of required screening.

Washington University in St. Louis is committed to providing a comprehensive and competitive benefits package to our employees. Benefits eligibility is subject to employment status, full-time equivalent (FTE) workload, and weekly standard hours. Please visit our website at https://hr.wustl.edu/benefits/ to view a summary of benefits.

Washington University in St. Louis is committed to the principles and practices of equal employment opportunity. It is the University's policy to provide equal opportunity and access to persons in all job titles without regard to race, ethnicity, color, national origin, citizenship (where prohibited by federal law), age, religion, sex, sexual orientation, gender identity or expression, disability, protected veteran status, or genetic information.