Staff Associate III

Description

The Department of Dermatology is seeking to hire a Staff Associate III for computational analysis of genomic datasets. The Staff Associate III will develop and lead a variety of bioinformatics analysis projects including integrative analysis of multiple genomic data including GWAS, gene expression, whole exome and genomic sequencing, among others.

Applicants should demonstrate strong statistical and biological programming proficiencies with proven expertise in genomic analysis and advanced knowledge of analytical methodologies.

Responsibilities include:

Functional Knowledge

• Applicants should demonstrate strong statistical and biological programming proficiencies with proven expertise in genomic analysis and advanced knowledge of analytical methodologies.
• Collaborate with biologists to design experiments and analyze data derived from several types of projects, in particular using 16S and metagenomics for microbiome sequencing and single cell RNA sequencing with TCR datasets.
• Write custom scripts for analysis of genomic data derived from high-throughput techniques.
• Manage databases, conduct statistical and genomic analysis, and participate in the preparation of manuscripts, grant applications and presentations.

Problem Solving

• Understanding of genomic data standards and formats (e.g., FASTQ, BAM, VCF) and proficiency in using tools for data manipulation and visualization.
• Write custom scripts for analysis of genomic data derived from high-throughput techniques.

Decision Making/Autonomy (Must equal 10)

• Level of supervision required, on a scale of 1 (least) to 10 (most) - #3
• •       Able to collaborate and work independently across projects and experience in multidisciplinary collaboration with researchers from other fields such as molecular biology, clinical research, and computational sciences to design and execute comprehensive genomics studies.
• Degree of independent judgment expected, on a scale of 1 (least) to 10 (most) - #7
  •            Collaborate with biologists to design experiments and analyze data.Conduct rigorous quality control procedures and comprehensive analysis to ensure data integrity and reliability.

Leadership

• Acts as a resource for new team members; manages schedule with PI's direction to ensure deadlines are met
• Training of other lab members in basic computational approaches for data analysis.

Technical Expertise

•      Strong statistical and biological programming proficiencies with proven expertise in genomic analysis and advanced knowledge of analytical methodologies.
• Experience in multidisciplinary collaboration with researchers from other fields such as molecular biology, clinical research, and computational sciences to design and execute comprehensive genomics studies.
• Ability to work autonomously in data analysis, seamlessly integrating findings from multiple research streams.
• Conducts rigorous quality control procedures and comprehensive analysis to ensure data integrity and reliability.
• Develop and lead a variety of bioinformatics analysis projects including integrative analysis of multiple genomic data including GWAS, gene expression, whole exome and genomic sequencing, among others.
• Understanding of genomic data standards and formats (e.g., FASTQ, BAM, VCF) and proficiency in using tools for data manipulation and visualization.

 Communication Skills

• Excellent oral and written communication skills and ability to teach basic computational methods to trainees.

 

 

Qualifications

Minimum Qualifications  

• Bachelor’s degree in [science], or related field
• 4-6 years of research experience 

Application Instructions

Please submit your CV, cover letter with statement of interest and contact information for 3 references with your online  application. 

In addition to the online application,  please email your C.V and cover letter to : lm2302@cumc.columbia.edu & amc65@cumc.columbia.edu. 

 

Equal Employment Opportunity Statement

Columbia University is an Equal Opportunity Employer / Disability / Veteran

Pay Transparency Disclosure

The salary of the finalist selected for this role will be set based on a variety of factors, including but not limited to departmental budgets, qualifications, experience, education, licenses, specialty, and training.  The above hiring range represents the University’s good faith