Postdoctoral Research Associate – Radiology Full-time

Postdoctoral Research Fellow In Neuroimaging, Artificial Intelligence, 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 second-highest NIH-funded among the Radiology Departments in the US. The position will work in the Neuroimaging Informatics and Artificial Intelligence (NeuroAI) lab under Dr. Ganesh Chand, Assistant Professor of Radiology, within WashU Medicine, 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.

Job Description

Primary Duties & Responsibilities:

• Perform quality checks of brain PET/MRI cognitive, clinical, genetic, and proteomic data and manage them in the data repository and computer servers.
• Run existing PET/MR brain image processing pipelines on the computer servers, produce the results, and communicate with the group members.
• Write computer codes for the above data modalities under the guidance of the team leader.
• Engage in the development and testing/validation of new quantitative AI algorithms and their applications to PET, MRI, EEG, behavioral, clinical, genetic, and proteomic data.
• Prepare documentation of existing and newly developed brain image analysis pipelines, algorithms, and quantitative methods.
• Assist the team in the manuscript preparation of the research findings.
• Support the team leader to fulfill the research objectives of their funded projects.
• Assist the team leader in generating preliminary results for grant funding proposals.
• Publish research findings in reputable scientific journals.
• Present research at conferences and contribute to grant applications.
• Mentor junior team members.
• Contribute to the overall research goals and objectives of the team.

Working Conditions:

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:

Base pay is 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

Education:

Ph.D., M.D. Or Equivalent Terminal Or Doctoral Degree.

Certifications /Professional Licenses :

No specific certification/professional license is required for this position.

Work Experience:

No specific work experience is required for this position.

Skills:

Not Applicable

Driver's License:

A driver's license is not required for this position.

More About This Job

Preferred Qualifications:

• PhD in quantitative field, such as biomedical physics, engineering, computer science, data science, bioinformatics, computational biology, computational neuroscience, statistical genomics, applied mathematics, biostatistics, or a related field.
• Strong computer skills (knowledge of Python, R, Python Libraries, MATLAB, statistical analysis packages, basic shell scripting, experience in Unix/Linux platform) and experiences with deep learning tools (e.g., PyTorch, TensorFLow, Keras), neuroimaging analysis tools (e.g., PMOD, SPM, FSL) and statistical genetics (GWAS, PRS, etc.) and related tools (e.g., PLINK).
• Experience with either 3D image processing (e.g., brain PET and MRI analysis) or statistical genomics (GWAS, PRS calculation, etc.) is highly preferred.
• Experience with multi-omics data analysis.
• Experience with neuroimaging-behavior and/or neuroimaging-genetics analysis.
• This position is ideal for a candidate who is familiar with emerging AI techniques, neuroimaging methods, and statistical genetics research.
• Strong communication (writing and speaking) and ability to collaborate in teamwork.

Questions

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

Accommodation

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.

Pre-Employment Screening

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.

Benefits Statement

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.

EEO Statement

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.