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Phd Computer Science Jobs in Ohio (NOW HIRING)

Medpace, Inc.

AI Scientist

Cincinnati, OH · On-site

PhD in Artificial Intelligence, Computer or Data Science, or related field; * Preferably several years of experience working with different AI capabilities and showcasing your passion both at work ...

Medpace, Inc.

AI Scientist

Cincinnati, OH · On-site

PhD in Artificial Intelligence, Computer or Data Science, or related field; * Preferably several years of experience working with different AI capabilities and showcasing your passion both at work ...

nou Systems, Inc.

M&S Developer

Dayton, OH · On-site

Preferred : • MS or PhD in Computer Science, Engineering, or related field. • 8+ years of experience with AFSIM or other mission-level modeling frameworks (NGTS, ITASE, World Simulation Framework ...

STR

Principal Product Lead (TL2)

Dayton, OH

$206K - $275K/yr

... or PhD with at least 10 years of experience (or equivalent experience) in a scientific field such as applied math, physics, electrical engineering, computer science, or data science. * Experience ...

Nationwide Children's Hospital

PhD or equivalent degree in relevant field of science, required. Licensure Requirement: (not ... Excellent computer skills. * Skills in qualitative and quantitative research methods. * Ability to ...

Nationwide Children's Hospital

PhD or equivalent degree in relevant field of science, required. Licensure Requirement: (not ... Excellent computer skills. * Skills in qualitative and quantitative research methods. * Ability to ...

Nationwide Children's Hospital

PhD or equivalent degree in relevant field of science, required. Licensure Requirement: (not ... Excellent computer skills. * Skills in qualitative and quantitative research methods. * Ability to ...

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Phd Computer Science information

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$53.7K

$79K

$93.2K

How much do phd computer science jobs pay per year?

As of Sep 3, 2026, the average yearly pay for phd computer science in Ohio is $79,011.00, according to ZipRecruiter salary data. Most workers in this role earn between $73,700.00 and $88,900.00 per year, depending on experience, location, and employer.

What is a PhD in computer science?

A PhD in Computer Science is the highest academic degree in the field, focused on advanced research and the creation of new knowledge in computing. It typically involves several years of coursework followed by original research culminating in a dissertation. Graduates often pursue careers in academia, research, or advanced industry roles that require deep technical expertise and problem-solving skills.

What are the key skills and qualifications needed to thrive as a PhD in computer science?

To thrive as a PhD in Computer Science, you need advanced expertise in algorithms, programming, and research methodologies, typically supported by a doctoral degree in computer science or a related field. Mastery of programming languages (such as Python, Java, or C++), data analysis tools, and familiarity with version control systems like Git are commonly required, along with experience in publishing academic research. Critical thinking, problem-solving, strong written and verbal communication, and perseverance are vital soft skills for success in research and collaboration. These skills and qualifications are essential for making significant contributions to the field, driving innovation, and effectively sharing knowledge with the academic and professional community.

What are some common challenges faced by PhD computer science students during their research?

PhD Computer Science students often encounter challenges such as defining a clear and impactful research problem, managing long-term projects with limited guidance, and coping with the pressure to publish in top-tier conferences or journals. Balancing coursework, teaching responsibilities, and research can also be demanding. Effective time management, networking with peers and mentors, and seeking regular feedback can help students navigate these challenges and achieve their academic goals.

Is a PhD worth it for computer science?

A PhD in computer science can lead to careers in research, academia, or specialized industry roles, often requiring advanced skills in algorithms, data analysis, and programming. While it offers opportunities for high-level positions and expertise, it typically involves several years of study and may not be necessary for most industry jobs, which often value practical experience and skills. The decision depends on career goals and the desire for research or teaching roles.

What can I do after a PhD in computer science?

A PhD in computer science prepares individuals for careers in academia, research, or advanced industry roles such as data scientist, machine learning engineer, or software architect. Graduates often pursue postdoctoral research, work in R&D departments, or obtain certifications in specialized tools and programming languages to enhance their expertise.

What jobs can I get with a PhD in computer science?

A PhD in computer science qualifies individuals for advanced roles such as research scientist, data scientist, machine learning engineer, or university professor. These positions often require strong analytical skills, programming expertise, and knowledge of algorithms, data structures, and AI tools. Graduates may work in academia, industry research labs, or technology companies focusing on innovation and development.

What are popular job titles related to Phd Computer Science jobs in Ohio?

For Phd Computer Science jobs in Ohio, the most frequently searched job titles are:

What job categories do people searching Phd Computer Science jobs in Ohio look for?

The top searched job categories for Phd Computer Science jobs in Ohio are:

What cities in Ohio are hiring for Phd Computer Science jobs?

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Phd Computer Science jobs near you
Infographic showing various Phd Computer Science job openings in Ohio as of August 2026, with employment types broken down into 100% Full Time. Highlights an 100% In-person job distribution, with an average salary of $79,011 per year, or $38 per hour.

BN31M1-Manager, Scientific AI Engineering & Data Science

Chemical Abstracts Service

Columbus, OH • On-site

Full-time

Posted 17 days ago

Job description

Position Overview
The Manager, Scientific AI Engineering & Data Science is a people-leadership role. The manager builds, grows, and leads a team of data scientists and AI engineers who develop the systems behind CAS's scientific discovery products - the retrieval, extraction, and reasoning that power CAS Newton℠ and CAS Connections, and internal platforms. The role sits in the Data Analytics & Insights (DAI) organization.
The manager's primary work is people: hiring, coaching, developing, and retaining data scientists and AI engineers, and creating the conditions for the team to do its best work. Technical direction, architecture, and roadmap delivery are owned by technical leads and product partners. The manager is expected to carry enough technical fluency to lead, coach, and mentor credibly - to understand the work, judge the quality of an engineer's contributions, and guide growth - but is not accountable for owning the technical roadmap or shipping it.
The role is not bounded by the manager's own set of direct reports. As DAI scales and elevates aggressively, the manager brings team-wide and enterprise-wide thinking to the role and steps in to drive cross-cutting initiatives as priorities dictate. The ideal candidate can speak fluently and confidently about the team's work to both internal and external audiences.
People Leadership & Talent
  • Own hiring for a growing team - sourcing, recruiting, interviewing, and evaluating talent.
  • Develop, retain, and motivate data scientists and AI engineers with scientific domain depth; shape and build the team.
  • Coach and mentor across levels, supporting both technical growth and career progression.
  • Manage performance and career development in line with the DAI career framework - job family, scope tier, and depth/breadth path.
  • Build bench strength, support succession, and sustain a healthy, inclusive, high-expectation team culture.
  • Match people to work thoughtfully, balancing team delivery with individual growth and job satisfaction.
Technical Fluency & Coaching
  • Maintain enough fluency across modern AI engineering - LLMs, agentic workflows and tool use, RAG, retrieval and extraction over scientific content, and evaluation - to lead and coach the team credibly.
  • Judge the quality of the team's technical work well enough to give meaningful feedback and guide development.
  • Understand the trustworthy-AI principles the team works to - including CAS's reliance on curated, provenanced scientific content, and the difference between acceptable model variability and genuine failure - well enough to reinforce them.
  • Partner with technical leads and product, who own technical direction, architecture, and roadmap.
Team Health & Enablement
  • Ensure the team is well-resourced, unblocked, and set up to succeed, working with technical leads and product on prioritization and staffing.
  • Remove organizational and people-level obstacles, and escalate and resolve issues that slow the team.
  • Support healthy operating practices - delivery rhythm, review, and production health - without owning roadmap outcomes.
Team-Wide Leadership & Enterprise Mindset
  • Bring team-wide and enterprise-wide thinking to the role, in service of scaling and elevating the organization aggressively.
  • Step in to lead and drive cross-cutting initiatives as priorities dictate - for example, specific programs with internal partners or targeted team-elevation efforts - unconstrained by the manager's own set of direct reports.
  • Speak fluently and confidently about the team's work to both internal and external audiences, including customers, partners, and the broader scientific community.
  • Approach the role with an ownership mindset that extends beyond the immediate team to the broader organization's success.
Partnership & Communication
  • Partner across Product, Technology, Content Operations, and other teams as the people leader for the team.
  • Represent the team's capacity, needs, and health to stakeholders and leadership.
  • Connect the team's people and capabilities to CAS's broader goals.
Qualifications
Education
  • Master's degree in a relevant technical or quantitative discipline (e.g., Computer Science, Applied Mathematics, Statistics, Data Science, Computational Chemistry, Physics, Bioinformatics), or equivalent experience.
  • A PhD and/or deep scientific domain expertise (chemistry, life sciences, materials science) is valued as a capability the person brings, and is not required.

Experience
  • 8+ years of relevant experience, including 3-5+ years developing people and leading technical teams.
  • Enough hands-on background in AI/ML engineering and data science to lead and coach the work credibly; direct roadmap or delivery ownership is not required at this level.
  • Familiarity with modern AI engineering - LLM-based, agentic, and large-scale retrieval and extraction systems.
  • Experience in scientific, chemical, pharmaceutical, or materials-science domains is desired.

Leadership & Competencies
  • Proven ability to hire, coach, grow, and retain technical talent.
  • Strong people-management, feedback, and career-development skills.
  • Team-wide and enterprise-wide perspective, and readiness to lead initiatives beyond one's own reporting line.
  • Ability to represent the team's work fluently and confidently to internal and external audiences.
  • Sound judgment on team health, culture, and prioritization.
  • Sufficient technical fluency to earn the trust of a team of data scientists and AI engineers.

Equal Opportunity Employer/Protected Veterans/Individuals with Disabilities
This employer is required to notify all applicants of their rights pursuant to federal employment laws. For further information, please review the Know Your Rights notice from the Department of Labor.

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