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Ai For Science Jobs in Virginia (NOW HIRING)

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 ...

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 ...

They are searching for a Data Scientist with expertise in data analysis and algorithm development to provide insights into applying AI for national security problems. Responsibilities : • Perform ...

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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.

Infographic showing various Ai For Science job openings in Virginia 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.
Postdoctoral Associate

Other

Posted 27 days ago


Virginia Tech rating

7.8

Company rating: 7.8 out of 10

Based on 65 frontline employees who took The Breakroom Quiz

225th of 612 rated colleges and universities


Job description

Postdoctoral Associate

Apply now Back to search results Job no: 536240
Work type: Research Faculty
Senior management: College of Engineering
Department: Computer Science
Location: Blacksburg, Virginia
Categories: Engineering, Research / Scientific

Job Description

Prof. Debswapna Bhattacharya's research group in the Department of Computer Science at Virginia Tech (https://people.cs.vt.edu/dbhattacharya/) seeks to recruit multiple postdoctoral associates in Artificial Intelligence (AI) in Biomolecular Modeling.
The postdoctoral associate will focus on developing and applying AI methodologies to drive advances in drug discovery and biomolecular design. The successful candidates will contribute significantly to the group's mission in leveraging AI for scientific discovery.
The successful candidates will conduct groundbreaking research that transforms current AI for Science paradigms focusing on multidisciplinary applications in biomolecular modeling and design, leading to a step-change in Scientific Machine Learning (SciML). They will be expected to collaborate with members of the group as well as other stakeholders and to perform modest service duties around missions of the group, such as training and engagement.

Required Qualifications

Ph.D. degree in Computer Science, Electrical and Computer Engineering, Computational Biology, Bioinformatics, Statistics, Mathematics, Biophysics, Physics, Chemistry, Biology or related fields.
PhD must be awarded no more than four years prior to the effective date of appointment with a minimum of one year eligibility remaining.
Substantial programming experience.
Excellent communication skills.

Preferred Qualifications

Demonstrated record of excellence in advancing artificial intelligence, characterized by a strong publication history in top-tier venues and a research background outlining significant contributions to AI that demonstrate high potential for research impact.
Published research experience in AI for scientific discovery and/or AI-driven biomolecular modeling and/or scientific machine learning.

Pay Band

{lPayScaleID}

Overtime Status

Exempt: Not eligible for overtime

Appointment Type

Restricted

Salary Information

$63,000-$73,000

Hours per week

40

Review Date

May 25, 2026

Additional Information

The successful candidate will be required to have a criminal conviction check.

About Virginia Tech

Dedicated to its motto, Ut Prosim (That I May Serve), Virginia Tech pushes the boundaries of knowledge by taking a hands-on, transdisciplinary approach to preparing scholars to be leaders and problem-solvers. A comprehensive land-grant institution that enhances the quality of life in Virginia and throughout the world, Virginia Tech is an inclusive community dedicated to knowledge, discovery, and creativity. The university offers more than 280 majors to a diverse enrollment of more than 36,000 undergraduate, graduate, and professional students in eight undergraduate colleges, a school of medicine, a veterinary medicine college, Graduate School, and Honors College. The university has a significant presence across Virginia, including Blacksburg, the greater Washington, D.C. area, the Health Sciences and Technology Campus in Roanoke, sites in Newport News and Richmond, and numerous Extension offices and research institutes. A leading global research institution, Virginia Tech conducts more than $650 million in research annually.

Virginia Tech endorses and encourages participation in professional development opportunities and university shared governance.  These valuable contributions to university shared governance provide important representation and perspective, along with opportunities for unique and impactful professional development.

Virginia Tech does not discriminate against employees, students, or applicants on the basis of age, color, disability, sex (including pregnancy), gender, gender identity, gender expression, genetic information, ethnicity or national origin, political affiliation, race, religion, sexual orientation, or military status, or otherwise discriminate against employees or applicants who inquire about, discuss, or disclose their compensation or the compensation of other employees or applicants, or on any other basis protected by law.

If you are an individual with a disability and desire an accommodation, please contact Joseph Morgan at jmorgan99@vt.edu during regular business hours at least 10 business days prior to the event.

Advertised: April 29, 2026
Applications close:

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About Virginia Tech

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Virginia Tech, guided by its motto "Ut Prosim" (That I May Serve), embraces a hands-on, interdisciplinary approach to educate scholars as leaders and problem-solvers. As a comprehensive land-grant institution, it enriches the quality of life in Virginia and worldwide, fostering an inclusive community focused on knowledge, discovery, and creativity. With over 280 majors, the university serves a diverse student body of more than 36,000 across undergraduate, graduate, and professional programs. Virginia Tech's presence extends throughout Virginia, including campuses in Northern Virginia, Roanoke, Newport News, and Richmond, along with multiple Extension offices and research centers. As a prominent global research institution, it conducts over $500 million in research annually.

Industry

Colleges, universities, and professional schools

Company size

5,001 - 10,000 Employees

Headquarters location

Blacksburg, VA, US

Year founded

1872

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