Postdoc position at Yale – whole genome sequencing and data science

American Society of Plumbing Engineers; New Haven (CT); On-site; USD 60,000 - 80,000; Full time

Job summary

A leading research institution invites applications for a postdoctoral position funded by NIH grants. The role focuses on analyzing rare and structural variants within human genomic data and involves integration of multi-omics data. Qualified candidates should have a Ph.D. in computational biology or a related field, programming skills, and strong quantitative abilities. Applicants must submit a cover letter and CV to the provided email.

Qualifications

• Ph.D. in relevant fields required.
• Experience with genomic data analysis essential.
• Professional programming skills needed.

Responsibilities

• Analyze rare and structural variants.
• Integrate multi-omics data.
• Develop novel statistical methods.

Skills

Experience with human genomic data analysis

Professional programming skills

Strong statistical and quantitative analysis skills

Excellent oral and written communication skills in English

Strong organizational and prioritization skills

Ability to work independently and collaboratively

Education

Ph.D. in computational biology, bioinformatics, or related fields

Tools

High-performance computing

Cloud computing

Job description

Overview

The Zhou Lab (PI: Hang Zhou) at the Department of Psychiatry and of Biomedical Informatics & Data Science at Yale University invites applications for a postdoctoral position funded by NIH grants.

The Zhou Lab focuses on uncovering the genetic mechanisms underlying substance use disorders and related diseases through the analysis of large-scale human genomic data. In recent years, the lab has led impactful genome-wide association and whole-exome sequencing studies in this field. With support from new NIH grants, the lab will expand this work by leveraging the largest whole-genome sequencing datasets available from major biobanks. The successful candidate will contribute to advancing our understanding of genetic etiology by analyzing rare and structural variants, integrating multi-omics data, applying advanced data science approaches, and developing novel statistical methods.

Responsibilities

The successful candidate will contribute to advancing our understanding of genetic etiology by analyzing rare and structural variants, integrating multi-omics data, applying advanced data science approaches, and developing novel statistical methods.

Preferred Qualifications

• Ph.D. in computational biology, bioinformatics, human genetics, biostatistics, data science, and related fields.
• Experience with human genomic data analysis.
• Professional programming skills, experience with high-performance computing, and cloud computing.
• Strong statistical and quantitative analysis skills.
• Highly motivated, dedicated, and detail-oriented.
• Willingness to explore novel research directions and methodologies.
• Excellent oral and written communication skills in English.
• Strong organizational and prioritization skills.
• Ability to work independently as well as collaboratively in a multidisciplinary environment.

Application Materials

Interested applicants should send the following materials to [e-mail]:

• Cover letter (including past research experience, a brief description of possible research interests, and the candidate's career goals)
• Curriculum vitae
• Contact information for three references