Postdoctoral Associate (Causal Inference)

Location: On-site in Cambridge, Massachusetts, United States

Salary: $70,000–$92,666.67 per year

Company

hirify.global of MIT and Harvard conducts interdisciplinary biomedical research in collaboration with Massachusetts General Hospital, Harvard Medical School, academic cohorts, biobanks, and industry partners.

What you will do

• Develop and apply causal inference methods to genetic, proteomic, epidemiological, and cardiovascular disease data.
• Conduct Mendelian randomization, colocalization, instrumental variable, negative control, and phenome-wide analyses.
• Integrate SomaScan, Olink, genome-wide array, whole-exome sequencing, and whole-genome sequencing data.
• Identify, prioritize, and validate druggable protein targets, including predicted efficacy and on-target safety.
• Build reproducible computational workflows and interpret complex genomic, proteomic, and clinical findings.
• Collaborate with computational scientists, physicians, cohort investigators, translational researchers, and industry partners; present findings and prepare scientific publications and grants.

Requirements

• PhD or equivalent doctoral degree in statistical genetics, genetic epidemiology, biostatistics, computational biology, bioinformatics, epidemiology, statistics, or a related field, with 0–2+ years of experience.
• Demonstrated experience applying causal inference methods to biomedical or population-based data.
• Experience analyzing large-scale human genetic or genomic datasets and using methods such as Mendelian randomization, colocalization, instrumental variable analysis, or negative control frameworks.
• Proficiency in R or Python, with strong quantitative, statistical, and computational skills.
• Ability to develop accurate, reproducible, and well-documented analytical workflows.
• Strong scientific writing, presentation, communication, organizational, and collaboration skills.

Nice to have

• Experience integrating genomic and proteomic datasets or working with SomaScan, Olink, or comparable platforms.
• Experience with genome-wide association studies, sequencing data, epidemiological cohorts, electronic health records, or hospital-based biobanks.
• Knowledge of cardiovascular genetics, cardiovascular epidemiology, therapeutic target identification, or drug development.
• Experience with high-performance computing, cloud-based analytical environments, or clinical and industry research collaborations.
• Peer-reviewed publications in a relevant quantitative or biomedical research area.

Culture & Benefits

• Interdisciplinary research environment spanning human genetics, proteomics, epidemiology, drug discovery, and disease biology.
• Opportunities to collaborate with academic, clinical, translational, and industry research partners.
• Medical, dental, vision, life, and disability insurance.
• 401(k), flexible spending and health savings accounts, paid holidays, winter closure, and paid time off.
• Parental and family care leave and an employee assistance program.