Bioinformatics Scientist
Job in
Cambridge, Middlesex County, Massachusetts, 02141, USA
Listed on 2026-06-20
Listing for:
Net2Source
Full Time
position Listed on 2026-06-20
Job specializations:
-
Research/Development
Research Scientist, Data Scientist, Clinical Research, Genetics / Genomics
Job Description & How to Apply Below
Source Inc.
Who We Are
Net2
Source Inc. isn't just another staffing company, we're a powerhouse of innovation, connecting top talent with the right opportunities. Recognized for 300% growth in the past three years, we operate in 34 countries with a global team of 5,500+. Our mission? To bridge the talent gap with precision—Right Talent. Right Time. Right Place. Right Price.
Job Title:
Bioinformatics Scientist - III (Senior)
Location:
Cambridge, MA 02141
Duration: 24 Months Contract
Pay Rate: $106.59/Hr on W2
Shift: Monday-Friday (8:00 AM to 5:00 PM) – 40.00 Hours/Week
(Job Details)
Contractor, Complex Disease Genetics
The Complex Disease Genetics (CDG) group within client's Data, AI and Genome Sciences (DAGS) Department is seeking a motivated scientist to support our Cambridge-based research initiatives in complex disease genetics. We welcome applications from scientists with a graduate degree (PhD or equivalent) in statistical genetics, genetic epidemiology, computational biology, biostatistics, or a related quantitative field with hands-on experience analyzing human genetics and multi-omics data.
client has invested in external partnerships and collaborative initiatives to accelerate innovation in drug discovery and development. The CDG group leverages large-scale data resources, such as Finn Gen, the Alliance for Genomic Discovery, Our Future Health, UK Biobank Pharma Proteomics Project, Open Targets, and other public and proprietary datasets, to advance client's drug development pipeline through human genetics. The candidate will contribute to the analysis of these large-scale datasets to support target identification and validation and the implementation of precision medicine strategies across therapeutic areas.
In this exciting role, you will:
- Perform statistical genetics analyses for target discovery and validation using human genetics and multi-omics data
- Support the development, implementation, and maintenance of analytical pipelines for reproducible genetic and genomic data analysis
- Conduct genetic association analyses using large-scale biobank data (e.g., UK Biobank, Finn Gen, Our Future Health, Alliance for Genomic Discovery)
- Integrate and analyze public and proprietary genetic association summary statistics and conduct meta-analyses
- Perform post-GWAS analyses to help elucidate causal mechanisms and prioritize gene targets (e.g., fine mapping, colocalization, Mendelian Randomization, TWAS, polygenic risk prediction)
- Assist in integrating genetic association findings with multi-omics data (e.g., RNA-seq, ATAC-seq, QTLs) to support target prioritization
- Stay current with new methods in statistical genetics and participate in evaluating and implementing emerging analytical techniques
- Collaborate with wet-lab biologists, disease area experts, and data scientists to support research and patient stratification strategies
- PhD (or equivalent) in statistical genetics, genetic epidemiology, population genetics, computational biology, bioinformatics, biostatistics, epidemiology, or a related quantitative discipline, with a minimum of 5 year of postdoctoral or equivalent research experience in complex disease genetics
- Research experience in human genetics, genomics, or related analysis, including genome-wide association studies (GWAS) and/or multi-omics analysis
- Familiarity with analytical pipelines and best practices for reproducibility and scalability in genetic data analysis
- Proficiency in programming languages commonly used in statistical genetics (e.g., R, Python, etc.)
- Experience working with large-scale datasets in could-based computing and high-performance computing environments
- Strong communication and interpersonal skills, with the ability to work effectively in multidisciplinary teams
- Experience with molecular phenotypes, such as transcriptomics or proteomics
- Interest or background in cardiovascular/metabolic diseases, immunology, neuroscience, or other complex diseases
- Experience with AI/ML methodology and/or application to genetics and omics analysis.
• Please add publication on the resume.
•…
To View & Apply for jobs on this site that accept applications from your location or country, tap the button below to make a Search.
(If this job is in fact in your jurisdiction, then you may be using a Proxy or VPN to access this site, and to progress further, you should change your connectivity to another mobile device or PC).
(If this job is in fact in your jurisdiction, then you may be using a Proxy or VPN to access this site, and to progress further, you should change your connectivity to another mobile device or PC).
Search for further Jobs Here:
×