Research Associate, Population Sciences - Department of Oncology

Wayne State University•Detroit, MI

1d•Onsite

About The Position

Wayne State University is searching for an experienced Research Associate, Population Sciences - Department of Oncology at its Detroit campus location. Wayne State is a premier, public, urban research university located in the heart of Detroit, Michigan where students from all backgrounds are offered a rich, high-quality education. Our deep-rooted commitment to excellence, collaboration, integrity, diversity and inclusion creates exceptional educational opportunities which prepare students for success in a global society. We seek a full-time, entry-level Research Associate with a strong foundation in computational genomics and a keen interest in cancer and epidemiology. This role offers the opportunity to contribute to various projects utilizing -omic data (e.g., GWAS, sequencing, RNA-seq, ATAC-seq) and integrating publicly available datasets from All of Us, UK Biobank, and dbGaP. The focus will be on understanding susceptibility to and survival following hematologic malignancies. This position is an excellent opportunity for someone looking to strengthen their computational skills while developing deeper expertise in cancer genomics and epidemiology.

Requirements

Bachelor's degree from an accredited college or university in public health, psychology, social sciences, nursing, biology, or related fields.
Requires advanced knowledge, predominantly intellectual in character, in a field of science or learning acquired by a prolonged course of specialized intellectual instruction.
Intermediate (3 to 4 years job-related experience)
Experience conducting clinical or human subjects research is preferred.
Experience with participant recruitment, informed consent, data collection, and maintenance of regulatory documentation is preferred.
Ability to work independently and manage multiple clinical research activities while adhering to study protocols, regulatory requirements, and timelines.
Ability to analyze, summarize, and interpret clinical research data and communicate findings effectively in reports and presentations.
Requires knowledge predominantly intellectual in character in a field of science or learning acquired through specialized instruction.
Knowledge of scientific integrity principles, responsible conduct of research, and human subject protections (e.g., IRB requirements, confidentiality standards).
Excellent time management, organizational, and documentation skills.
Strong interpersonal and communication skills, with demonstrated ability to interact professionally with research participants, clinical staff, and multidisciplinary research teams.
Proficiency in Microsoft Office software (Word, Excel, PowerPoint) and familiarity with clinical research databases or electronic data capture systems is preferred.
Ability to recruit and communicate effectively with diverse populations, including medically underserved communities.
Ability to identify workflow issues and recommend process improvements.

Nice To Haves

MS in Statistical Genetics, Human Genetics with Computational Biology, Quantitative Epidemiology, or a related field OR BS with 3+ years of work experience demonstrating an equivalent MS-level understanding of subject matter and skill set.
Experience with data QC, analysis, and interpretation of human biological data.
Prior experience in human genetics (single variant and gene-based association analysis using WES/WGS/array genotyping data) is ideal, but candidates with relevant experience in adjacent fields and a willingness to learn are encouraged to apply.
Basic understanding of EHR data (e.g., UK Biobank, All of Us) and genomics databases (e.g., gnomAD, 1000 Genomes, TOPMed).
Prior hands-on experience with these resources is preferred but not required.
Proficiency in R required; Python is also acceptable.
Working knowledge of Unix/Linux and cloud computing environments.
Strong interest in developing written and verbal communication skills for conveying analysis results to experts and non-experts.
Some experience with peer-reviewed publications and/or conference presentations is preferred.

Responsibilities

Support the design and implementation of clinical research protocols involving human subjects.
Recruit and screen study participants through approved methods, including outreach, surveys, and interviews.
Conduct study visits and collect clinical and research data in compliance with Institutional Review Board (IRB), regulatory, and protocol requirements.
Communicate regularly with the Principal Investigator and research team regarding study progress and participant status.
Collect, enter, and maintain accurate clinical and research data, including outcomes, surveys, and case report forms.
Monitor data quality and completeness.
Perform preliminary data analysis and generate graphs, charts, and tables to summarize results in accordance with study protocols.
Proofread and verify research data and documentation for accuracy.
Prepare and assist with presentations of research findings for professional, scientific, and academic conferences.
Organize and summarize study results for submission to peer-reviewed journals.
Assist in drafting, factchecking, editing, and proofreading scientific manuscripts, study reports, and regulatory documents.
Maintain organized research records and study files in accordance with regulatory and institutional requirements.
Coordinate study materials and supplies, and support documentation for audits, monitoring visits, and regulatory submissions.
Ensure workspaces remain organized and compliant with confidentiality and data security standards.
Perform other related duties as assigned.
Under the direction of the PI, design, execute, and interpret genetic studies using diverse quantitative and binary traits from large-scale cohorts.
Collaborate with colleagues in various multi-PI research consortia, including presenting and discussing analysis results.
Stay up to date with advances in human genetic analysis methods and be able to discuss these developments with both experts and non-experts.