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Ai For Science Jobs in Texas (NOW HIRING)

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Ai For Science information

What is AI for Science?

AI for Science refers to the application of artificial intelligence and machine learning techniques to accelerate scientific discovery and research. By leveraging large datasets, complex models, and advanced computational methods, AI helps scientists analyze data, identify patterns, simulate experiments, and make predictions across various scientific fields such as biology, chemistry, physics, and climate science. This approach can significantly speed up research, uncover new insights, and solve problems that were previously too complex or time-consuming for traditional methods.

How does collaboration typically work between AI for Science professionals and domain experts in research teams?

AI for Science professionals frequently work closely with experts in fields such as biology, chemistry, or physics to identify scientific problems that can benefit from machine learning techniques. Collaboration usually involves regular meetings to translate complex scientific challenges into data-driven models, sharing domain knowledge, and iteratively refining solutions. Effective communication and a willingness to bridge gaps between computational and scientific perspectives are essential. This interdisciplinary teamwork not only enhances the impact of AI solutions but also fosters ongoing learning and innovation.

What are the key skills and qualifications needed to thrive as an AI for Science specialist, and why are they important?

To thrive as an AI for Science Specialist, you need a strong background in computer science, mathematics, and scientific domains, often supported by advanced degrees (e.g., PhD or MSc) in relevant fields. Proficiency with machine learning frameworks (such as TensorFlow or PyTorch), scientific computing tools, and familiarity with high-performance computing environments are typically required. Critical thinking, interdisciplinary collaboration, and effective communication are crucial soft skills for translating scientific problems into AI solutions. These skills are vital for developing innovative models, ensuring research rigor, and enabling impactful scientific discoveries.

What is the difference between Ai For Science vs Data Scientist?

AspectAi For ScienceData Scientist
Required CredentialsDegree in Science, Computer Science, or related fields; knowledge of AI and machine learningDegree in Statistics, Computer Science, or related fields; strong programming skills
Work EnvironmentResearch labs, scientific institutions, tech companies focused on scientific applicationsCorporate, tech firms, finance, healthcare, and other industries analyzing data
Industry UsageApplied to scientific research, simulations, and experimental data analysisUsed for data analysis, predictive modeling, and business insights

Ai For Science focuses on applying AI techniques to scientific research and experiments, often requiring a background in science and specialized knowledge of AI. Data Scientists analyze large datasets across various industries to extract insights and build models. While both roles involve AI and data analysis, Ai For Science is more research-oriented within scientific contexts, whereas Data Scientists work across diverse sectors on data-driven decision making.

What cities in Texas are hiring for Ai For Science jobs?

Cities in Texas with the most Ai For Science job openings:

Infographic showing various Ai For Science job openings in Texas as of August 2026, with employment types broken down into 1% As Needed, 79% Full Time, 18% Part Time, and 2% Contract. Highlights an 73% Physical, 4% Hybrid, and 23% Remote job distribution.

Senior Machine Learning Research Scientist, Secure AI Lab

Arlington, TX โ€ข On-site

$140 - $190/hr

Other

Posted 22 days ago


Job description

Jobs / Senior Machine Learning Research Scientist, Secure AI Lab

Senior Machine Learning Research Scientist, Secure AI Lab

Full-time

About the Role

At the SEI AI Division, we conduct research in applied artificial intelligence and the engineering questions related to the practical design and implementation of AI technologies and systems. We currently lead a community-wide movement to mature the discipline of AI Engineering for Defense and National Security.As our government customers adopt AI and machine learning toprovideleap-ahead mission capabilities, weโ€ข build real-world, mission-scale AI capabilities through solving practical engineering problemsโ€ข discover and define the processes, practices, and tools to support operationalizing AI for robust, secure, scalable, and human-centered mission capabilitiesโ€ข prepare our customers to be ready for the unique challenges of adopting, deploying, using, andmaintainingAI capabilitiesโ€ข identifyand investigate emerging AI and AI-adjacent technologies that are rapidly transforming the technology landscapeAre you creative, curious, energetic, collaborative, technology-focused, and hard-working? Are you interested in making a difference by bringing innovation to government organizations and beyond? Apply to join our team.Overview:As a Senior Machine LearningResearch Scientist,you will specialize inconductingresearch into the vulnerabilities of AIandML algorithms and securing against those vulnerabilities.TheSecure AILab within the SEIโ€™s AI Division focuses on improving the security and robustness of AI systems. As part of the world-class research community at Carnegie Mellon University, theSecure AILabconducts and appliescutting-edgeresearch toprotectAI systems fromadversaries who aim to manipulatethe systemto learn, do, or revealsomething itisnโ€™tsupposed to.TheSecure AILab consists of machine learning research scientists, machine learning engineers, and software developers who work together to solve problems in the following areas:

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