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$40.4K

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How much do environmental informatics jobs pay per year?

As of May 31, 2026, the average yearly pay for environmental informatics in Indiana is $93,642.00, according to ZipRecruiter salary data. Most workers in this role earn between $66,600.00 and $116,600.00 per year, depending on experience, location, and employer.

What is an Environmental Informatics job?

An Environmental Informatics job involves using data, technology, and computational tools to analyze and solve environmental challenges. Professionals in this field collect, process, and interpret environmental data from sources like satellite imagery, sensors, and databases. They work in areas such as climate modeling, natural resource management, and pollution monitoring to support decision-making. Environmental informatics specialists often collaborate with scientists, policymakers, and organizations to develop sustainable solutions using data-driven insights.

What are the key skills and qualifications needed to thrive in the Environmental Informatics position, and why are they important?

To thrive in Environmental Informatics, you need a solid background in environmental science, data analysis, and geospatial technologies, often supported by a relevant degree such as environmental science, computer science, or geography. Expertise in GIS software (e.g., ArcGIS, QGIS), programming languages (such as Python or R), and data management systems is commonly required, along with industry certifications like GISP being a plus. Strong problem-solving abilities, communication skills, and collaborative mindset help professionals translate complex data into actionable insights and work effectively with multidisciplinary teams. These combined skills enable accurate environmental data interpretation and informed decision-making for sustainable resource management and policy development.

What are the typical daily responsibilities of someone working in Environmental Informatics?

Professionals in Environmental Informatics typically spend their days collecting, managing, and analyzing large datasets related to environmental phenomena such as air quality, land use, or water resources. They often use GIS software, database management tools, and programming languages to clean, visualize, and interpret data, then collaborate with scientists, policymakers, and stakeholders to present their findings. Daily tasks might also include developing or maintaining environmental monitoring systems and contributing to research reports or grant proposals. This role involves both independent technical work and teamwork, offering a balance of analytical and collaborative activities.
More about Environmental Informatics jobs
What are popular job titles related to Environmental Informatics jobs in Indiana? For Environmental Informatics jobs in Indiana, the most frequently searched job titles are:
What job categories do people searching Environmental Informatics jobs in Indiana look for? The top searched job categories for Environmental Informatics jobs in Indiana are:
What cities in Indiana are hiring for Environmental Informatics jobs? Cities in Indiana with the most Environmental Informatics job openings:
Environmental Informatics jobs near you
Infographic showing various Environmental Informatics job openings in Indiana as of May 2026, with employment types broken down into 7% As Needed, 14% Full Time, 72% Part Time, and 7% Nights. Highlights an 100% Physical job distribution, with an average salary of $93,642 per year, or $45 per hour.
Postdoctoral Fellow in Biostatistics & Health Data Science

Postdoctoral Fellow in Biostatistics & Health Data Science

Indiana University

Bloomington, IN • On-site

$45.30K - $61.50K/yr

Full-time

Posted 17 days ago

Job description

Posting Details
Position Details
Title
Postdoctoral Fellow in Biostatistics & Health Data Science
Specific Title
Appointment Type
Postdoctoral Fellow
Department
IUSM - Biostatistics
Campus
IU School of Medicine Indianapolis
Position Summary
Research Context & Opportunity-Modern healthcare increasingly depends on integrating data across hospitals, registries, cohorts, and public health systems. Yet semantic heterogeneity-differences in terminology, structure, and logic-remains a central barrier to reusability, interoperability, and reproducibility.
This postdoctoral position addresses a fundamental and timely research question:
How can Large Language Models (LLMs) and intelligent agents support transparent, scalable, and auditable clinical data harmonization?
We are particularly interested in:
  • LLM-driven systems for aligning real-world health data to standards like OMOP CDM, FHIR, and UMLS
  • Agent-based workflows that explain, refine, and adapt semantic mappings over time
  • Hybrid architectures that combine knowledge-grounded reasoning with flexible machine learning
  • Tools that reduce manual burden while preserving traceability and clinical interpretability

This position offers the opportunity to publish novel methods, work with real messy multi-source data, and contribute to infrastructure supporting population-level research and health equity.
The postdoctoral fellow will be based in the Department of Biostatistics and Health Data Science at Indiana University School of Medicine, in close collaboration with the Regenstrief Institute, a nationally renowned center for health informatics research and real-world data infrastructure.
  • Indiana University is home to one of the largest medical schools in the U.S., with extensive collaborations across informatics, clinical departments, and health systems (IU Health, Eskenazi Health, etc.).
  • Regenstrief Institute is internationally recognized for its leadership in data standards (e.g., LOINC), clinical data networks (e.g., Indiana Network for Patient Care), and health information infrastructure.
  • This environment supports both methodological research and operational implementation across state, national, and multi-institutional networks (e.g., NIH, OHDSI, PCORnet, ACT Network).

Our Team's Approach-
We are not a pure research group. We operate at the interface of research and health data operations, building methods that not only publish but also deploy. We handle real clinical and public health data problems where ambiguity, variation, and scale are the norm-not the exception.
We welcome postdocs who want to drive innovation while engaging deeply with practical, meaningful data challenges.
Responsibilities
  • Design and implement LLM-based methods for clinical data harmonization, semantic normalization, and ontology alignment
  • Develop multi-agent or RAG-style (retrieval-augmented generation) workflows for schema matching and terminology mapping
  • Collaborate with national and multi-institutional initiatives in data integration and standardization
  • Support open-source tooling, reproducible pipelines, and standards-based approaches (e.g., OMOP, FHIR, UMLS)
  • Lead or support manuscript preparation and dissemination at top informatics and AI venues
  • Contribute to grant development and proposal writing

What We Offer-
  • A collaborative environment at the intersection of real-world data, applied AI, and translational science
  • Opportunities to work across academic, clinical, and public health settings
  • Mentorship and support toward independent research or career development in academia or industry
  • Competitive salary and benefits through Indiana University
  • A culture that values both scientific innovation and practical impact

The Indianapolis Campus is the focal point of health professions education at Indiana University, and the School of Medicine is the country's second largest allopathic medical school. Indianapolis consistently ranks high nationally on many of the "best places to live" lists and has an economy that is growing in the life sciences arena. In addition, it has always been one of the cities with the lowest cost of living. Carmel, Indy's northern neighbor, was recently named as the best mid-sized city in the country.
IUSM is committed to being a welcoming campus community and we seek candidates whose research, teaching, and community engagement efforts contribute to robust learning and working environments for all students, staff, and faculty. We invite individuals who will join us in our mission to improve health equity and well-being for all throughout the state of Indiana.
Indianapolis is the capital and most populous city in the State of Indiana. It is growing economically thanks to a strong corporate base anchored by the life sciences. Indiana is home to one of the largest concentrations of health sciences companies in the nation. Indianapolis has a sophisticated blend of charm and culture with a wonderful balance of business and leisure. The growing residential base is supported by rich amenities and quality of life - the city possesses a variety of professional sports, arts venues and outdoor recreation areas. Residents of this dynamic city, and surrounding suburbs, enjoy leading educational systems and top-ranked universities, paired with a diverse population. Indianapolis International Airport is a top-ranked international airport, being named "Best Airport in North America" by Airports Council International for many years. For additional information on life in Indy: https://faculty.medicine.iu.edu/relocationThe search will continue until the positions are filled.
Basic Qualifications
Required Qualifications:
  • Ph.D. (by start date) in Computer Science, Biomedical Informatics, Health Data Science, Biostatistics, or a closely related area.
  • Strong ML/deep learning foundation plus expertise in at least one of: multimodal learning, time-series modeling, or NLP.
  • Demonstrated working experience with healthcare data (e.g., EHR, clinical text, imaging, omics).
  • Proficiency in Python and ML tooling (e.g., PyTorch, scikit-learn), version control (Git), and experiment tracking (e.g., Weights & Biases).
  • Excellent written and oral communication skills, and ability to collaborate with multidisciplinary teams.

Department Contact for Questions
Professor Jiang Bian via email at: bianj@regenstrief.org
Additional Qualifications
Preferred Qualifications:
  • Experience with concept normalization, ontology mapping, or schema alignment
  • Familiarity with LLM agents, tool-augmented reasoning, or hybrid rules + LLM systems
  • Record of publications in relevant domains (informatics, machine learning, AI, knowledge representation)
  • Experience with multi-site data harmonization or federated data environments

Special Instructions
Priority Application Review Deadline
Expected Start Date
Posting Number
IUSM-02358-2026

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