Postdoctoral Scholar

Tufts University; Medford (MA); On-site; USD 61,000 - 74,000; Full time

Job summary

The Center for Applied Brain and Cognitive Sciences at Tufts University in Medford, MA seeks a Post-Doctoral Scholar to advance data analysis and quantitative modeling of behavioral, cognitive, and physiological data. You will apply multilevel modeling, Bayesian methods, and data visualization to support cognitive science research.

You will mentor junior researchers, develop analysis pipelines in R and Python, and contribute to publications and presentations at professional meetings.

Qualifications

• PhD in Psychology, Cognitive Science, Statistics, or related field (recently completed or soon to be completed).
• Strong foundational expertise in statistical methods including: regression (linear/logistic/lasso/ridge/elastic net), mixed models, PCA/FA, non-parametric methods, and simulation-based inference.
• High proficiency in R and/or Python for data analysis, including statistical modeling, visualization, and diagnostics.
• Demonstrated experience with or foundational knowledge of Bayesian modeling, including model comparison, posterior estimation, and priors (e.g., using brms or pymc).
• 1-2 years of research experience involving meta-analysis and systematic reviews (can be acquired during graduate studies).
• Experience conducting power analyses (frequentist and/or Bayesian), effect size estimation, assumption testing, and data imputation.
• Excellent analytical, organizational, and teamwork skills.
• Excellent written and verbal communication skills, with an interest in cross-disciplinary collaboration.
• Strong publication/presentation record involving statistical analysis of cognitive or behavioral data.

Responsibilities

• Provide statistical support across ongoing research projects using frequentist and Bayesian methods.
• Conduct statistical modeling with mixed effects and regression frameworks.
• Develop code and pipelines in R (metafor, tidyverse, brms) and Python (scikit-learn, pymc, pandas).
• Mentor junior researchers in rigorous data preprocessing and analysis.
• Conduct data-driven research to support CABCS objectives in cognitive domains.
• Analyze cognitive and physiological data; write papers and create presentations.
• Assist in managing laboratory resources and equipment.
• Support collaborations with internal and external researchers.
• Deliver presentations at professional meetings and author publications.

Skills

Statistical methods

Regression analysis

Mixed models

Bayesian methods

Power analysis

Data visualization

Data cleaning

Teamwork

Education

PhD in Psychology, Cognitive Science, Statistics, or related field

Tools

R

Python

brms

pymc

scikit-learn

pandas

Job description

Overview

The Center for Applied Brain and Cognitive Sciences is a collaborative research initiative that brings together interdisciplinary teams of scientists and engineers to advance applied brain and cognitive sciences. The Center conducts cutting-edge research to measure, predict, and enhance human cognitive capabilities, performance, and human-system interactions in complex, high-stakes, real-world environments including military.

What You'll Do

To support applied cognitive science research at the Center for Applied Brain and Cognitive Sciences. Specifically, a Post-Doctoral Scholar is needed to support the lab's data analysis and quantitative modeling efforts to examine behavioral, cognitive, and physiological data. This includes the application of multilevel modeling, data visualization, and statistical diagnostics, as well as assisting in the mentorship of junior researchers and students in statistical methodology and rigorous best practices for data analytic techniques.

• Provide statistical support across ongoing research projects and serve as a resource for applying frequentist and Bayesian methods, including data analysis, diagnostics, model validation, and interpretation.
• Conduct statistical modeling using foundational approaches, including mixed effect/multilevel models and regression frameworks.
• Develop and document code and pipelines/workflows using R (e.g., metafor, tidyverse, brms) and Python (e.g., scikit-learn, pymc, pandas).
• Assist in training and mentoring junior team members on best practices for rigorous data preprocessing and analysis, including power analysis, data imputation, bootstrapping/non-parametric techniques, and meta-analysis.
• Conduct data-driven research in support of CABCS objectives under the guidance of the Principal Investigator, particularly in cognitive and applied psychology domains.
• Conduct studies involving cognitive and physiological modalities, analyze data, write papers/reports, and design presentations.
• Support the PI and senior researchers in the management of associated laboratory resources and equipment.
• Assist in managing research projects and supporting collaborations with internal and external researchers.
• Deliver presentations and demonstrations of work and represent CABCS at professional meetings.
• Author/co-author peer-reviewed publications.

What We're Looking For

Knowledge and experience typically acquired by:

• PhD in Psychology, Cognitive Science, Statistics, or a related field (recently completed or soon to be completed).
• Strong foundational expertise in statistical methods including: regression (linear/logistic/lasso/ridge/elastic net), mixed models, PCA/FA, non-parametric methods, and simulation-based inference.
• High proficiency in R and/or Python for data analysis, including statistical modeling, visualization, and diagnostics.
• Demonstrated experience with or foundational knowledge of Bayesian modeling, including model comparison, posterior estimation, and priors (e.g., using brms or pymc).
• 1-2 years of research experience involving meta-analysis and systematic reviews (can be acquired during graduate studies).
• Experience conducting power analyses (frequentist and/or Bayesian), effect size estimation, assumption testing, and data imputation.
• Excellent analytical, organizational, and teamwork skills.
• Excellent written and verbal communication skills, with an interest in cross-disciplinary collaboration.
• Strong publication/presentation record involving statistical analysis of cognitive or behavioral data.

Preferred Qualifications

• Experience or familiarity with advanced methodologies, including structural equation modeling (SEM), machine learning techniques, and psychometric network analysis.
• Experience supporting military-focused research or human performance studies.
• Experience conducting behavioral experiments involving AR/VR technologies.
• Background in UX research for applied systems or application development.
• Expertise in psychometric modeling, including confirmatory factor analysis (CFA) and measurement invariance testing; experience applying these methods to assess the validity of cognitive assessments across populations (e.g., WAIS-IV).
• Experience teaching or mentoring in statistics and research methods at the undergraduate or graduate level, with emphasis on applied instruction in R and/or Python.

Pay Range

Minimum $67,500.00, Midpoint $67,500.00, Maximum $67,500.00
Salary is based on related experience, expertise, and internal equity; generally, new hires can expect pay between the minimum and midpoint of the range.