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Causal Inference Machine Learning Postdoctoral Jobs in Louisiana

Ochsner Health

Senior AI Scientists

New Orleans, LA · On-site

Define and evolve Ochsner's artificial intelligence and machine learning (AI/ML) strategy across ... causal inference, and experiment design. Provide technical mentorship through design reviews, code ...

Ochsner Health

Senior AI Scientists

New Orleans, LA · On-site

Define and evolve Ochsner's artificial intelligence and machine learning (AI/ML) strategy across ... causal inference, and experiment design. Provide technical mentorship through design reviews, code ...

Block

... causal reasoning, agentic systems, and product intelligence. The goal is not simply to build ... Preference and goal inference * Learning when intervention creates value versus friction Agentic ...

Block

... causal reasoning, agentic systems, and product intelligence. The goal is not simply to build ... Preference and goal inference * Learning when intervention creates value versus friction Agentic ...

Block

... causal reasoning, agentic systems, and product intelligence. The goal is not simply to build ... Preference and goal inference * Learning when intervention creates value versus friction Agentic ...

Block

... causal reasoning, agentic systems, and product intelligence. The goal is not simply to build ... Preference and goal inference * Learning when intervention creates value versus friction Agentic ...

Block

... causal reasoning, agentic systems, and product intelligence. The goal is not simply to build ... Preference and goal inference * Learning when intervention creates value versus friction Agentic ...

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Causal Inference Machine Learning Postdoctoral information

What is a causal inference machine learning postdoctoral researcher?

A Causal Inference Machine Learning Postdoctoral researcher is a scientist who specializes in developing and applying machine learning methods to understand cause-and-effect relationships in data. They typically hold a recent PhD in statistics, computer science, economics, or a related field, and work in academic or industry research settings. Their work involves designing experiments, analyzing complex datasets, and creating models that can infer causal relationships, which are crucial for making robust predictions and informed decisions. This role often collaborates with interdisciplinary teams to apply these techniques to domains such as healthcare, social science, or economics.

What are the key skills and qualifications needed to thrive as a causal inference machine learning postdoctoral researcher?

To thrive as a Causal Inference Machine Learning Postdoctoral researcher, you need a strong background in statistics, causal inference methodologies, and advanced machine learning, usually evidenced by a PhD in a relevant field. Familiarity with programming languages such as Python or R, experience using statistical software (e.g., TensorFlow, PyTorch, Stan), and knowledge of causal inference libraries are typically required. Outstanding analytical thinking, problem-solving abilities, and strong communication skills help you collaborate effectively and explain complex concepts to diverse audiences. These skills and qualifications are vital for advancing research, deriving actionable insights from data, and contributing to impactful scientific discoveries.

What are some common challenges faced by causal inference machine learning postdoctoral researchers when integrating causal models with real-world data?

Causal Inference Machine Learning Postdoctoral researchers often encounter challenges such as dealing with unobserved confounding variables, ensuring data quality, and addressing biases inherent in observational datasets. Integrating advanced machine learning techniques with causal inference frameworks requires careful consideration of model assumptions and validation methods. Collaboration with domain experts is essential to properly interpret results and to translate findings into actionable insights, especially in interdisciplinary settings like healthcare or social sciences.

What is the difference between Causal Inference Machine Learning Postdoctoral vs Data Scientist?

AspectCausal Inference Machine Learning PostdoctoralData Scientist
Required CredentialsPhD in statistics, machine learning, or related fieldBachelor's or Master's in data science, computer science, or related field
Work EnvironmentAcademic research, research labs, universitiesCorporate, tech companies, startups
Industry UsageResearch, academia, specialized industry projectsBusiness analytics, product development, data-driven decision making
Common Search/ComparisonYesYes

The main difference is that Causal Inference Machine Learning Postdoctoral roles focus on academic research and developing new methods in causal inference, often requiring a PhD. Data Scientists typically work in industry, applying existing models to solve business problems, with a focus on data analysis and visualization. While both roles involve machine learning, the postdoctoral position emphasizes research and theory, whereas data science emphasizes practical application.

Is it difficult to get a causal inference machine learning postdoctoral position?

Securing a causal inference machine learning postdoctoral position can be competitive due to specialized skills required, such as expertise in statistical methods, programming (e.g., Python or R), and a strong research background. Candidates with relevant publications, strong recommendations, and experience in machine learning frameworks often have better chances, but the availability of such positions varies by institution and funding.

What job categories do people searching Causal Inference Machine Learning Postdoctoral jobs in Louisiana look for?

The top searched job categories for Causal Inference Machine Learning Postdoctoral jobs in Louisiana are:

Causal Inference Machine Learning Postdoctoral jobs near you
Infographic showing various Causal Inference Machine Learning Postdoctoral job openings in Louisiana as of September 2026, with employment types broken down into 1% Internship, 1% As Needed, 74% Full Time, 22% Part Time, and 2% Contract. Highlights an 82% Physical, 2% Hybrid, and 16% Remote job distribution.

Postdoctoral Remote Sensing Scientist

Lafayette, LA • On-site, Remote

Cherokee Federal
Architectural Services • 1 - 5K employees
Learn more about Cherokee Federalexternal

Full-time

Medical, Dental, Vision, Retirement

Posted 15 days ago

Job description


Postdoctoral Remote Sensing Scientist
Cherokee United Services is seeking a Postdoctoral Remote Sensing Scientist in Lafayette, Louisiana. This role advances research on coastal wetland change and ecosystem responses to extreme events at landscape, regional, and global scales.
Compensation & Benefits:
Compensation is commensurate with experience.
Full-time benefits include Medical, Dental, Vision, 401(k), and other possible benefits as provided. Benefits are subject to change with or without notice.
Postdoctoral Remote Sensing Scientist Responsibilities Include:
• Conduct scientific literature reviews related to remote sensing, GIS analysis, landscape ecology, coastal wetland ecosystems, and habitats being mapped or analyzed.
• Advance the production and analysis of remotely sensed data to assess coastal wetland change, support restoration planning, evaluate restoration effectiveness, and inform future ecosystem predictions.
• Acquire, develop, organize, document, and analyze long-term remote-sensing data to measure spatial and temporal change in coastal wetland ecosystems.
• Execute experiments using remotely sensed imagery, spatial-analysis outputs, and innovative geospatial methods.
• Apply machine-learning and deep-learning techniques to remote-sensing imagery and spatial data, as appropriate to project needs.
• Integrate existing geospatial information, including historical climate data, vegetation-change products, and other environmental datasets, with newly developed remote-sensing products.
• Apply knowledge of landscape ecology and coastal wetland ecosystem dynamics for advancing understanding of coastal wetland changes using geospatial analyses and remote sensing.
• Produce custom geospatial products and analytical outputs that support research on the ecological effects of extreme events occurring in recent decades.
• Develop and maintain complete, accurate documentation for project activities, datasets, data-production processes, technical methods, and analytical procedures.
• Maintain project status records, timekeeping documentation, data logs, analytical code, and version-controlled project materials.
• Produce Federal Geographic Data Committee (FGDC)-compliant metadata for all required deliverables.
• Prepare publication-ready maps, figures, tables, datasets, data releases, reports, and manuscripts for peer-reviewed journal publication.
• Summarize and communicate research findings through technical reports, journal articles, conference presentations, and presentations to USGS staff, cooperators, partners, and customers.
• Provide a leadership role in preparing for and facilitating meetings with research partners.
• Participate in project meetings, technical discussions, and other coordination activities as needed.
• Assist with technical aspects of proposal development, as assigned.
• Use professional experience and sound judgment to recommend next steps, identify issues, and propose solutions during project execution.
• Perform work independently and in accordance with established standard operating procedures, quality standards, and project requirements.
• Support field-based data-collection activities, when required.
• Follow all applicable federal information-security, privacy, property-protection, and facility-security requirements.
• Perform other job-related duties as assigned.
Postdoctoral Remote Sensing Scientist Experience, Education, Skills, and Abilities Requested:
• Doctoral degree in geography or a closely related field required or strongly preferred.
• Academic emphasis or demonstrated expertise in GIS, remote sensing, landscape ecology, coastal wetlands, environmental science, geography, or a related discipline required.
• One to three years of experience working in a scientific or research setting preferred.
• Demonstrated experience developing, processing, analyzing, and interpreting remote-sensing data products required.
• Experience using GIS, spatial analysis, geospatial datasets, satellite or aerial imagery, and environmental data required.
• Experience applying machine-learning and/or deep-learning techniques to remote-sensing or spatial-analysis projects preferred.
• Knowledge of coastal wetland ecosystem dynamics and coastal ecosystem change preferred.
• Ability to integrate historical climate data, vegetation-change products, and other geospatial datasets into scientific analyses.
• Experience conducting analyses across landscape, regional, and/or global geographic scales preferred.
• Demonstrated ability to design, execute, document, and interpret scientific experiments using remotely sensed imagery and spatial-analysis outputs.
• Strong experience preparing technical reports, peer-reviewed manuscripts, scientific figures, tables, maps, data products, and conference presentations.
• Familiarity with USGS or federal scientific-data practices, including data management, reproducible methods, technical documentation, and metadata development.
• Ability to create FGDC-compliant metadata for datasets and other required deliverables.
• Demonstrated ability to maintain accurate data logs, project records, documentation, and code in a version-control repository.
• Strong written, verbal, and interpersonal communication skills, including the ability to present complex scientific findings clearly to technical and nontechnical audiences.
• Ability to effectively collaborate with federal scientists, project partners, cooperators, customers, and stakeholders.
• Ability to lead or support the planning and facilitation of partner meetings.
• Ability to work independently, exercise sound judgment, manage competing priorities, and deliver accurate work on schedule.
• Strong attention to detail and commitment to data quality, documentation accuracy, customer specifications, and timely project delivery.
• Ability to successfully complete a federal background investigation and maintain required access credentials.
Company Information:
Cherokee Federal is a trusted team of government contracting professionals who rapidly build innovative and advanced solutions across environmental science, immigration, national security and intelligence, cybersecurity, health care, and logistics. Cherokee Federal is owned by Cherokee Nation Businesses, and 100% of profits support Cherokee Nation citizens through health care, education, and job creation. To learn more, visit cherokee-federal.com.
#CherokeeFederal #LI-RA2
Cherokee Federal is a military-friendly employer. Veterans and active military members transitioning to civilian careers are encouraged to apply.
• 5 Keywords:
o Remote Sensing
o Geographic Information Systems (GIS)
o Coastal Wetlands
o Machine Learning
o Landscape Ecology
• 5 Similar Job Titles:
o Remote Sensing Scientist
o Geospatial Research Scientist
o Coastal Wetland Scientist
o GIS Research Scientist
o Landscape Ecologist
Legal Disclaimer: All qualified applicants will receive consideration for employment without regard to protected veteran status, disability, or any other status protected under applicable federal, state, or local law. Many of our job openings require access to government buildings or military installations.
Cherokee Federal logo

About Cherokee Federal

Sourced by ZipRecruiter

Cherokee Federal - a division of Cherokee Nation Businesses - is a team of tribally owned federal contracting companies focused on building solutions, solving complex challenges, and serving the nation's mission around the globe for more than 60 federal clients. Our team of companies manages nearly 1,000 projects of all sizes across the construction, consulting, engineering and manufacturing, health, and technology portfolios. Since 2012, the Cherokee Federal team of companies has won more than $5 billion in government contracts. Our 3,000+ employees work in 26 countries, 50 states and 2 U.S. territories. Why choose Cherokee Federal? Visit our website and learn about the great reasons to join our team. cherokee-federal.com

Industry

Architectural services

Company size

1,001 - 5,000 Employees

Headquarters location

Tulsa, OK, US

Year founded

1969

Social media

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