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Ai For Science Jobs in Florida (NOW HIRING)

The role requires deep technical expertise across AI for science protein and antibody design, AI-driven molecular dynamics, agentic AI and autonomous research systems, clinical trial simulations ...

Active research areas include protein and antibody design, novel AI approaches to molecular dynamics simulations, agentic AI and autonomous systems for science, clinical trial simulations, virtual ...

Join the Foundational Modeling team at Splunk, where we advance the state of AI for highvolume ... Collaborate with engineering, product, and data science teams to understand requirements ...

Join the Foundational Modeling team at Splunk, where we advance the state of AI for highvolume ... Collaborate with engineering, product, and data science teams to understand requirements ...

Our mission is to lower the barrier for organizations and people to get value out of AI ... Must understand data analysis and how to apply data science solutions into end products. Required ...

Recruiting for this role ends on 7/31/2026. Work you'll do As an AI and Data Science Engineer III on the AI & Data team, you will be responsible for driving technology-focused client delivery across ...

Agentic AI, AI & Data Science Engineer

Tampa, FL · On-site

$108K - $129K/yr

Recruiting for this role ends on 7/31/2026. Work you'll do As an AI and Data Science Engineer III on the AI & Data team, you will be responsible for driving technology-focused client delivery across ...

MLOps & DevOps Collaboration Work with engineering and product teams to implement best practices for deploying and maintaining AI models in production. * Manage the execution of data science ...

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Ai For Science information

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.

Which 3 jobs will survive AI?

For roles related to AI for science, jobs such as research scientists, data analysts, and laboratory technicians are likely to persist as they require specialized knowledge, critical thinking, and hands-on experimentation that AI cannot fully replicate. These positions often involve complex problem-solving, interpretation of experimental data, and domain-specific expertise. Continuous learning and proficiency with AI tools can enhance job security in these fields.

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.

What AI can I use for science?

AI for science involves using machine learning models, data analysis tools, and neural networks to analyze scientific data, make predictions, and automate research tasks. Common tools include TensorFlow, PyTorch, and specialized platforms like DeepMind or IBM Watson, often requiring programming skills in Python and knowledge of data science. These AI applications support fields such as biology, chemistry, physics, and environmental science.

Can AI take over science jobs?

AI for science roles involves automating data analysis, modeling, and research tasks, which can enhance productivity but are unlikely to fully replace scientists. Human expertise is essential for designing experiments, interpreting results, and making complex decisions. AI tools are typically used to support scientists rather than replace them entirely.

What is a $900000 AI job?

A $900,000 AI job typically refers to a high-level position in artificial intelligence, such as a senior AI researcher, machine learning director, or AI executive, often requiring advanced skills, extensive experience, and leadership responsibilities. These roles may involve overseeing AI projects, developing innovative algorithms, and working with cutting-edge tools, and they usually offer compensation in the upper echelons of the industry. Such salaries are more common in large tech companies or specialized AI firms.

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 are popular job titles related to Ai For Science jobs in Florida? For Ai For Science jobs in Florida, the most frequently searched job titles are:
What cities in Florida are hiring for Ai For Science jobs? Cities in Florida with the most Ai For Science job openings:
Infographic showing various Ai For Science job openings in Florida as of July 2026, with employment types broken down into 72% Full Time, 13% Part Time, and 15% Contract. Highlights an 87% In-person, and 13% Remote job distribution.

University Of Alabama At Birmingham rating

7.7

Company rating: 7.7 out of 10

Based on 44 frontline employees who took The Breakroom Quiz

254th of 614 rated colleges and universities


Job description

Position Summary

The University of Alabama at Birmingham invites qualified candidates to apply for a Scientist III position in the Systems Pharmacology AI Research Center (SPARC) department. The candidate will frequently encounter high-level complexities that demand sharp judgment and rigorous decision-making. The role requires deep technical expertise across AI for science protein and antibody design, AI-driven molecular dynamics, agentic AI and autonomous research systems, clinical trial simulations, virtual cell modeling, multi-modal drug discovery, and retrosynthesis; combined with a strategic orientation toward research planning, execution, and translation. The selected candidate will lead the development of novel AI models and software systems that form essential components of SPARC's AI-accelerated drug discovery pipeline, direct in silico computational studies, and lead lab-in-the-loop collaborations with UAB, regional, and national experimental partners. Obtaining AI drug discovery research funding as a Co-Principal Investigator or Co-Investigator on extramural grant proposals is a major and recurring responsibility, alongside leading SPARC service activities not covered by existing external funding and authoring scientific manuscripts, progress reports, and grant documentation. Active research areas include protein and antibody design, novel AI approaches to molecular dynamics simulations, agentic AI and autonomous systems for science, clinical trial simulations, virtual cell modeling, multi-modal drug discovery, retrosynthesis, and AI for science more broadly. Excellent office, programming, and communication skills are essential. SPARC offers GPU/HPC infrastructure, large biomedical data assets, deep clinical partnerships, and direct opportunities to translate methodological advances into impact across the UAB School of Medicine.

General Responsibilities

  • To interpret, organize, execute and coordinate research assignments.

  • To formulate and conduct research on problems of considerable scope and complexity.

  • To explore subject area and define scope and selection of problems for investigation through conceptually related studies or series of projects of lesser scope.

Key Duties & Responsibilities

  1. Research Direction: Deciding the focus of the lab's research agenda, including selection of research projects that align with both current scientific needs and future potential.

  2. Methodological Choices: Making choices about research methodologies, including the selection of appropriate AI algorithms, data sources, and experimental designs that maximize the potential for impactful findings.

  3. Resource Allocation: Determining how to allocate limited resources, such as lab equipment, funding, and personnel time, in a manner that optimally supports ongoing and future research efforts.

  4. Team Leadership: Making decisions about the mentoring and development of research staff, prioritizing areas for skills development and guiding research assistants and interns toward achieving lab and project goals.

  5. Funding Opportunities: Identifying and prioritizing grant and external funding opportunities that will offer the highest yield for the lab's objectives, including making decisions on when and how to pursue these opportunities.

  6. Commercial Partnerships: Judging the viability and potential of industrial and commercial collaborations and deciding the terms under which these collaborations will proceed to ensure the mutual benefit of all stakeholders.

  7. Publication and Dissemination: Deciding when research findings are robust and significant enough for publication and choosing the appropriate platforms and journals for dissemination to ensure maximum impact.

  8. Perform other duties as assigned.

Salary Range:   $ 80,300- $ 133,300

Qualifications

Doctor of Philosophy, D.V.M. or M.D. degree in a related field and six (6) years of related experience OR M.D. and Master's degree and four (4) years of related experience required. Work experience may NOT substitute for education requirement.

Preferences

  • Doctor of Philosophy (PhD) in biomedical informatics, computing, computer science, data science, artificial intelligence, or a closely related field. PhD completed within the last 10 years preferred.

  • AI/ML Expertise: Deep proficiency with modern machine learning, including deep learning, transformers, graph neural networks, generative models, and foundation models and their application across biomedical and chemical sciences. 

  • Molecular and Structural AI: Hands-on experience with novel AI approaches to molecular dynamics simulations, protein/antibody structure prediction and design, retrosynthesis, and multi-modal drug discovery. 

  • Programming and Engineering: Strong Python skills (PyTorch / JAX / TensorFlow); comfortable with HPC and GPU workflows, modern MLOps, and reproducible computational pipelines.

  • Agentic and Autonomous AI: Experience designing agentic AI workflows or autonomous research systems for science, including LLM tool-use, retrieval-augmented pipelines, and self-driving experimentation loops.   

  • Statistical and Causal Reasoning: Strong statistical foundations including hypothesis testing, Bayesian inference, uncertainty quantification, and causal modeling for biomedical data.  

  • Biomedical Data at Scale: Familiarity with large-scale biomedical, omics, imaging, clinical-trial, and chemical datasets, including data integration across modalities for virtual-cell and multi-modal drug-discovery applications.

Key Skills

  • Leadership: Ability to lead, guide, and mentor a team of researchers and students. 

  • Communication: Excellent verbal and written communication skills for publishing research, delivering presentations, and grant writing. 

  • Collaboration: Ability to work efficiently in a multidisciplinary environment, with the capability to integrate various scientific domains. 

  • Problem-Solving: Strong analytical thinking and the ability to approach complex scientific problems creatively. 

  • Time Management: Ability to manage multiple projects and deadlines effectively.


 

UAB is an Equal Employment/Equal Educational Opportunity Institution dedicated to providing equal opportunities and equal access to all individuals regardless of race, color, religion, ethnic or national origin, sex (including pregnancy), genetic information, age, disability, and veteran's status. As required by Title IX, UAB prohibits sex discrimination in any education program or activity that it operates. Individuals may report concerns or questions to UAB's Assistant Vice President and Senior Title IX Coordinator. The Title IX notice of nondiscrimination is located at uab.edu/titleix.


What University Of Alabama At Birmingham employees say

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About University of Alabama at Birmingham

Sourced by ZipRecruiter

The University of Alabama at Birmingham is the heartbeat of Birmingham and an integral medical leader in the Southeast. The Birmingham campus is within walking distance of some of the best parks, entertainment, and dining in the region. UAB's three regional campuses expand their academic reach and responsibilities in addition to educating physicians in rural and underserved areas of the state. UAB is experiencing major and sustained investment and growth, due both to its exceptional research faculty and its culture of collaboration. Through concerted and strategic investments in its clinical and research enterprise, UAB has undergone an amazing transformation in the past five years and has strengthened its status and reputation as a leader in medical training, biomedical discovery, innovation, and patient care.

Industry

Colleges, universities, and professional schools

Company size

10,000+ Employees

Headquarters location

Birmingham, AL, US

Year founded

1859