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Quantitative Research Assistant Jobs in Indiana (NOW HIRING)

Kelly Services

R&D Analytical Analyst

Indianapolis, IN · On-site

$21/hr

... degradants (quantitative and qualitative). * Instrumentation: Learn and operate analytical ... Method Validation Support: Assist with method validation experiments as needed. * Automation & High ...

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Quantitative Research Assistant information

What is a quantitative research assistant?

Quantitative research assistants are professionals who support research projects by collecting, analyzing, and interpreting numerical data. They often use statistical software to manage datasets, perform statistical analysis, and help prepare reports or presentations based on their findings. These assistants typically work in academic, scientific, or business settings and collaborate closely with lead researchers or data scientists. Their work helps ensure that research conclusions are based on rigorous and accurate quantitative analysis.

What are the key skills and qualifications needed to thrive as a quantitative research assistant?

To thrive as a Quantitative Research Assistant, you need strong analytical skills, proficiency in statistical methods, and a relevant degree in fields like mathematics, statistics, or economics. Familiarity with statistical software such as R, Stata, SPSS, or Python, as well as experience with data management systems, is typically required. Attention to detail, problem-solving abilities, and effective communication are key soft skills that set candidates apart. These skills are essential for ensuring the accuracy, reliability, and clarity of research findings, which directly impact the quality and credibility of quantitative research projects.

What are some common challenges quantitative research assistants face when managing large datasets, and how can these be addressed?

Quantitative Research Assistants often work with large, complex datasets that can present challenges such as data cleaning, ensuring accuracy, and maintaining data integrity. Handling missing values, outliers, or inconsistent formats requires attention to detail and strong technical skills in statistical software like R, Python, or SPSS. Collaborating closely with research teams can help clarify data requirements and resolve ambiguities early on. Regularly documenting procedures and validating data at each stage helps minimize errors and ensures reliable analysis results.

What is the difference between Quantitative Research Assistant vs Data Analyst?

AspectQuantitative Research AssistantData Analyst
Required CredentialsBachelor's degree in statistics, economics, or related fieldBachelor's or master's in data science, statistics, or related field
Work EnvironmentResearch institutions, universities, market research firmsCorporate, finance, healthcare, or tech companies
Employer & Industry UsageAcademic and research settings, market research firmsBusiness analytics, finance, marketing departments
Common Search & ComparisonOften compared for data handling and research tasksCompared for data processing and reporting roles

The main difference is that Quantitative Research Assistants focus on supporting research projects with data collection and analysis in academic or research settings, while Data Analysts typically work in business environments analyzing data to inform decisions. Both roles require strong quantitative skills and similar educational backgrounds, but their work environments and primary objectives differ.

What are the most commonly searched types of Quantitative Research jobs in Indiana?

The most popular types of Quantitative Research jobs in Indiana are:

What are popular job titles related to Quantitative Research Assistant jobs in Indiana?

For Quantitative Research Assistant jobs in Indiana, the most frequently searched job titles are:

What job categories do people searching Quantitative Research Assistant jobs in Indiana look for?

The top searched job categories for Quantitative Research Assistant jobs in Indiana are:

What cities in Indiana are hiring for Quantitative Research Assistant jobs?

Cities in Indiana with the most Quantitative Research Assistant job openings:

Quantitative Research Assistant jobs near you

Postdoctoral Research Fellow, Midwest Regional Energy Symbiosis

Notre Dame, IN • On-site

University of Notre Dame
Colleges, Universities, and Professional Schools • 5 - 10K employees
Learn more about University of Notre Dameexternal

$48K - $65K/yr

Full-time

Re-posted 22 days ago

University Of Notre Dame rating

7.4

Company rating: 7.4 out of 10

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Job description

Description
The University of Notre Dame invites applications for a Postdoctoral Research Fellow to join a collaborative, interdisciplinary team of researchers from Notre Dame, Indiana University, Purdue University, and the University of Wisconsin to develop and pilot an AI-enabled material flow and industrial symbiosis framework that connects energy, water, and resource loops. This innovative research engages the Midwest's strong presence in manufacturing, agricultural landscapes, construction activity, and freshwater resources as a living regional laboratory to develop transferable methods for mapping, modeling, and evaluating industrial symbiosis opportunities across interconnected energy, water, material, agricultural, industrial, and construction systems. The postdoctoral fellow will serve as the central analytical and coordination lead for the project, working under the technical guidance of the PI and co-investigators.
The postdoctoral fellow will contribute to key project outcomes, including, but not limited to:
  • Developing an innovative industrial symbiosis framework that outlines short-term feasible and long-term transformative cross-sector exchanges.
  • Creating a transparent AI-enabled and replicable methodology that can be adapted to other Midwestern and U.S. regions to support energy-water-resource engineering and circular economy research.
  • Coordinating meetings and work with faculty teams and other research assistants.
  • Lead the co-authorship of interdisciplinary, peer-reviewed publications in high impact journals and develop the foundation for future grant proposals.

The postdoctoral fellow will assume the following key responsibilities:
  • Compiling, managing, and integrating geospatial and infrastructure datasets related to industrial facilities, manufacturing processes, water and wastewater systems, solid waste streams, agricultural production, energy systems, construction-related material demand, and secondary resource flows.
  • Developing regional material flow inventories that identify major sources, sinks, transformation points, and potential exchange pathways.
  • Conducting industrial symbiosis screening to identify feasible cross-sector resource exchanges.
  • Supporting the development of transparent AI-enabled assessment methods.
  • Conducting simplified material flow analysis, life-cycle assessment, and techno-economic screening to evaluate selected symbiosis pathways.
  • Preparing technical briefs, maps, diagrams, scenario portfolios, and visualizations to support team coordination and communication with public and private sector partners.
  • Producing first drafts of scholarly manuscripts and contributing technical content, preliminary results, figures, and supporting analyses for follow-on grant proposals.

This search is conducted with leadership from Notre Dame's Just Transformations to Sustainability Initiative, a University-wide effort to build a sustainable future where people and nature flourish together. The Initiative supports an interdisciplinary cohort of postdoctoral scholars dedicated to advancing sustainability research grounded in the principles of integral ecology and integral human development.
This is a full-time position available with an initial appointment of one-year, renewable for an additional year on the basis of satisfactory performance and availability of funding.
Qualifications
Required Qualifcations:
  • Ph.D. (in hand by the starting date) in industrial ecology, environmental engineering, civil and environmental engineering, systems engineering, sustainable manufacturing, urban systems, architecture/engineering, environmental science, geography, data science, or a closely related field.
  • Demonstrated research experience in one or more of the following areas: material flow analysis, life-cycle assessment, techno-economic analysis, industrial symbiosis, circular economy, resource recovery, waste management, water-energy-food systems, sustainable manufacturing, or low-carbon construction/material systems.
  • Strong quantitative and data-integration skills, including experience working with geospatial data, infrastructure datasets, environmental inventories, or regional-scale resource-flow data.
  • Expertise with LCA/MFA tools, databases, or methods; experience with software such as SimaPro, openLCA, Brightway, Python, R, GIS platforms, or related analytical tools is desirable.
  • Experience with AI, machine learning, optimization, spatial analysis, scenario modeling, or decision-support methods is strongly preferred, especially when applied in transparent, interpretable, or policy-relevant contexts.
  • Ability to synthesize complex multi-sector information into clear analytical outputs, including maps, figures, diagrams, tables, technical memos, and scholarly manuscripts.
  • Strong writing, communication, and coordination skills, with the ability to work across a multi-institutional and interdisciplinary research team.
  • Interest in regional sustainability, circular resource engineering, industrial ecology, and applied research that supports energy-water-resource loop closure.

Application Instructions
Applications will be reviewed on a rolling basis starting on September 1, 2026, and will continue until the position is filled.
Interested applicants should submit the following materials at their earliest convenience:
  1. A two page cover letter that describes in detail their research interests, background and qualifications for the role.
  2. A detailed curriculum vitae.
  3. Three recent publications or dissertation chapters.
  4. Contact information for at least three references.

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