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Full Time Artificial Intelligence Cognitive Science Jobs

Vivum AI

Computational Neuroethologist

Bloomington, IN · On-site

... how artificial intelligence powers autonomous systems and robotics. They are seeking a highly ... Required : • Strong background in neuroethology • Strong background in cognitive science • ...

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Full Time Artificial Intelligence Cognitive Science information

What are the key skills and qualifications needed to thrive as a full time artificial intelligence cognitive science professional?

To excel in a Full Time Artificial Intelligence Cognitive Science role, a strong background in computer science, mathematics, psychology, and neuroscience is essential, often supported by an advanced degree in a related field. Familiarity with machine learning frameworks (such as TensorFlow or PyTorch), programming languages (like Python), and cognitive modeling tools is typically required. Critical thinking, creativity, and effective communication are crucial soft skills for interdisciplinary collaboration and innovation. These skills enable professionals to develop intelligent systems that effectively model and understand human cognition, driving advancements in AI applications.

What is a full time artificial intelligence cognitive science professional?

Full Time Artificial Intelligence Cognitive Science jobs focus on developing and applying AI technologies using principles from cognitive science, such as perception, learning, and reasoning. Professionals in these roles work on building intelligent systems that can mimic or augment human cognitive abilities. They may work in research, product development, or applied AI, collaborating with interdisciplinary teams to solve complex problems. These positions are typically full-time and may be found in industries like technology, healthcare, education, and more.

What is the difference between Full Time Artificial Intelligence Cognitive Science vs Data Scientist?

AspectFull Time Artificial Intelligence Cognitive ScienceData Scientist
Required CredentialsMaster's or PhD in AI, Cognitive Science, Computer ScienceBachelor's or Master's in Data Science, Statistics, Computer Science
Work EnvironmentResearch labs, tech companies, academiaBusiness, tech firms, analytics departments
Industry UsageAI development, cognitive modeling, researchData analysis, predictive modeling, business insights

Full Time Artificial Intelligence Cognitive Science focuses on understanding human cognition and developing AI systems, often requiring advanced degrees in AI or cognitive science. Data Scientists analyze data to extract insights, typically with backgrounds in statistics or data analysis. While both roles involve data and algorithms, AI Cognitive Science emphasizes research and AI development, whereas Data Science centers on data-driven decision making.

What does a full time artificial intelligence cognitive science professional do?

In a full-time Artificial Intelligence Cognitive Science position, you can expect to work on interdisciplinary projects that combine AI algorithms with insights from neuroscience, psychology, and linguistics. Common responsibilities include designing experiments to model human cognition, developing or optimizing machine learning models, and interpreting data to understand how machines can mimic or augment human thought processes. Collaboration is frequent, often involving cross-functional teams of data scientists, engineers, and cognitive researchers. This role offers opportunities to contribute to cutting-edge applications such as natural language processing, decision-making systems, and human-computer interaction.
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Full Time Artificial Intelligence Cognitive Science jobs near you
Infographic showing various Full Time Artificial Intelligence Cognitive Science job openings in the United States as of August 2026, with employment types broken down into 1% Internship, 1% As Needed, 72% Full Time, 23% Part Time, and 3% Contract. Highlights an 76% Physical, 3% Hybrid, and 21% Remote job distribution.

Artificial Intelligence Technical Lead

Avani Technology Solutions, Inc.

Dallas, TX • On-site

Full-time

Re-posted 12 days ago

Job description

Artificial Intelligence Technical Lead
Dallas, TX or Indianapolis, IN
2 Years
No C2C at this moment. Any visa works
• Exposure to course work or projects in Machine Learning Libraries, Tensor Flow, Natural Language Processing (NLP) and Machine Vision
• At least 4 years' experience in application development using Python, R,
Python and R needed coming from a Java background or .NET Background.
Scala is a plus.
• At least 2 years' experience in handling data and working with database tools, e.g. SQL, Hadoop, Spark
• In this role, candidate will design, develop and create tools to get insight through application of machine learning, artificial intelligence and cognitive computing to build process automation platform. Candidate will be expected to be hands on as well as guide and mentor new analysts in the team.
Responsibilities:
• Work as a team lead in Automation and AI offering to understand underlying business problem and solutions
• Build Artificial Intelligence platform (Application development) through identification of appropriate machine learning algorithms
• As a team lead candidate will be working with various team members such as business analyst, data engineers, quality analyst, SMEs and with application developers
• Assess, document and articulate the effectiveness of different AI approaches
• Ability to create and train the models in machine learning methods including deep learning and ensembles
• Should be enthusiastic to learn and use APIs (like text analytics, language understanding etc.) to build AI and Cognitive applications
• Familiarity working with unstructured data
• Demonstrated experience solving business problems and delivering solutions to the client
• Ability to work in a multiple team and vendor environment
• Ability to work in an ambiguous and virtual environment
Qualifications
• Proven ability to work creatively and analytically in a problem-solving environment
• Desire to work in an information systems environment
• Excellent communication (written and oral) and interpersonal skills
• Excellent leadership and management skills
• Ability to work using Agile delivery methodology
• Master's Degree in a quantitative discipline such as mathematics, statistics, process engineering or operations research is preferred

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