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Ai For Science Jobs in Virginia (NOW HIRING)

Virginia Tech

Postdoctoral Associate

Blacksburg, VA · On-site

... AI for Science paradigms focusing on multidisciplinary applications in biomolecular modeling and design, leading to a step-change in Scientific Machine Learning (SciML). • Collaborating with ...

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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.

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.

Which AI for science is best?

The best AI tools for science depend on the specific application, such as data analysis, modeling, or simulation. Popular options include TensorFlow, PyTorch, and specialized platforms like DeepMind or IBM Watson, which are used by researchers to develop and deploy AI models in scientific research. Proficiency in programming languages like Python and understanding of machine learning concepts are essential for roles in AI for science.

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 Virginia? For Ai For Science jobs in Virginia, the most frequently searched job titles are:
What job categories do people searching Ai For Science jobs in Virginia look for? The top searched job categories for Ai For Science jobs in Virginia are:
What cities in Virginia are hiring for Ai For Science jobs? Cities in Virginia with the most Ai For Science job openings:
Ai For Science jobs near you
Infographic showing various Ai For Science job openings in Virginia as of August 2026, with employment types broken down into 78% Full Time, and 22% Part Time. Highlights an 100% In-person job distribution.

Postdoctoral Associate

Virginia Tech

Blacksburg, VA • On-site

Full-time

Re-posted 14 days ago

Virginia Tech rating

7.8

Company rating: 7.8 out of 10

Based on 65 frontline employees who took The Breakroom Quiz

229th of 618 rated colleges and universities

Job description

Job Summary:
Virginia Tech is a leading global research institution dedicated to knowledge, discovery, and creativity. They are seeking multiple postdoctoral associates in Artificial Intelligence focused on biomolecular modeling, contributing to drug discovery and scientific advancements.
Responsibilities:
• Developing and applying AI methodologies to drive advances in drug discovery and biomolecular design.
• Conducting 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).
• Collaborating with members of the group as well as other stakeholders.
• Performing modest service duties around missions of the group, such as training and engagement.
Qualifications:
Required:
• 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:
• 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.
Company:
Virginia Tech is a public research university that offers a range of academic programs and conducts research across various fields. Founded in 1872, the company is headquartered in Blacksburg, USA, with a team of 5001-10000 employees. The company is currently Late Stage.

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About Virginia Tech

Sourced by ZipRecruiter

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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