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Phd Science Jobs in Georgia (NOW HIRING)

Emory University is a leading research university that fosters excellence and attracts world-class talent to innovate today and prepare leaders for the future. We welcome candidates who can ...

Emory University is a leading research university that fosters excellence and attracts world-class talent to innovate today and prepare leaders for the future. We welcome candidates who can ...

Discover Your Career at Emory University Emory University is a leading research university that fosters excellence and attracts world-class talent to innovate today and prepare leaders for the future.

Discover Your Career at Emory University Emory University is a leading research university that fosters excellence and attracts world-class talent to innovate today and prepare leaders for the future.

Discover Your Career at Emory University Emory University is a leading research university that fosters excellence and attracts world-class talent to innovate today and prepare leaders for the future.

Discover Your Career at Emory University Emory University is a leading research university that fosters excellence and attracts world-class talent to innovate today and prepare leaders for the future.

We tap into the power of emerging technologies and scientific breakthroughs to create solutions and ... PhD from an accredited college/university is preferred * Proficiency in delivering analytics ...

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Phd Science information

See Georgia salary details

$20.7K

$40.9K

$66.7K

How much do phd science jobs pay per year?

As of May 28, 2026, the average yearly pay for phd science in Georgia is $40,860.00, according to ZipRecruiter salary data. Most workers in this role earn between $32,500.00 and $43,900.00 per year, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive as a PhD Scientist, and why are they important?

To thrive as a PhD Scientist, you need advanced expertise in your scientific discipline, strong research skills, and a doctoral degree (PhD) in a relevant field. Familiarity with specialized laboratory equipment, data analysis software (such as R or Python), and publication processes is typically required. Critical thinking, attention to detail, and effective communication are vital soft skills for presenting complex findings and collaborating with peers. These skills and qualifications are crucial for driving innovative research, producing publishable results, and contributing to scientific advancement.

What are the typical career advancement paths for someone with a PhD in Science in academia and industry?

Individuals with a PhD in Science often start in postdoctoral or entry-level research positions, where they build specialized expertise and publish their findings. In academia, advancement typically involves progressing to assistant, associate, and full professor roles, with additional opportunities to lead research groups or departments. In industry, PhD holders can move into senior scientist, project manager, or R&D director roles, with the potential to transition into leadership, policy, or consulting positions. Building a strong professional network, publishing impactful research, and developing leadership skills are key to advancing in both sectors.

What is a PhD in Science?

A PhD in Science is the highest academic degree awarded in scientific fields such as biology, chemistry, physics, or environmental science. It typically involves several years of advanced coursework, followed by original research that contributes new knowledge to the field. Graduates must defend a dissertation before a panel of experts. Earning a PhD in Science prepares individuals for careers in academia, research, industry, and leadership roles within scientific organizations.

What is the difference between Phd Science vs Data Scientist?

AspectPhd ScienceData Scientist
Required CredentialsPhD in a scientific field, research experienceBachelor's or Master's in CS, stats, or related field; often a PhD preferred
Work EnvironmentResearch labs, academia, industry R&DTech companies, finance, healthcare, consulting
Industry UsageResearch roles, scientific analysis, product developmentData analysis, machine learning, predictive modeling

While both roles involve analytical skills and data handling, Phd Science focuses on scientific research and experimentation, often in academic or R&D settings. Data Scientists primarily analyze large datasets to inform business decisions and develop models in industry environments. The key difference lies in their application areas and typical work environments.

What cities in Georgia are hiring for Phd Science jobs? Cities in Georgia with the most Phd Science job openings:
Machine Learning Engineer - PhD or PhD Candidate (Near Completion)

Machine Learning Engineer - PhD or PhD Candidate (Near Completion)

Optimal Inc.

Embry Hills, GA • On-site

Contractor

This job post has expired today. Applications are no longer accepted.


Job description


Candidates with only a Master's degree will not be considered.

Minimum qualification: PhD (completed or currently pursuing with expected completion in the near term) in a relevant technical field.

This is an urgent requirement with an anticipated start date within 2 weeks.
Priority will be given to candidates who can interview promptly and begin within two weeks of selection.

We are seeking a highly motivated Machine Learning / Deep Learning Research Engineer with strong expertise in Machine Learning, Deep Learning, Computer Vision, and AI research. This role is intended exclusively for PhD graduates or candidates near completion from reputable universities. Candidates with a strong academic research background in Machine Learning, Artificial Intelligence, Computer Vision, Data Science, or related fields are encouraged to apply.

Research experience gained during a PhD program will be considered equivalent to professional industry experience.

This is an urgent hiring requirement, and we are actively seeking candidates who can start within the next 2 weeks.

Education Requirement

PhD in Computer Science, Computer Engineering, Electrical Engineering, Artificial Intelligence, Machine Learning, Data Science, or a related technical field
Candidates currently pursuing a PhD with anticipated graduation within the next 3-6 months are also encouraged to apply
Only PhD candidates will be considered for this role
Candidates with only a Master's degree will not be considered


Key Responsibilities
Design, develop, train, and optimize Machine Learning and Deep Learning models for real-world applications
Own the complete ML lifecycle including data collection, annotation, preprocessing, model training, fine-tuning, evaluation, optimization, and deployment
Develop and deploy advanced deep learning architectures including CNNs, LSTMs, ConvLSTMs, Graph Neural Networks (GNNs), Reinforcement Learning, and Transformer-based models
Conduct experiments, evaluate model performance, and drive continuous algorithmic improvements
Work with large-scale datasets for model training, validation, and testing
Optimize and deploy AI models for scalable and efficient real-world applications
Translate research concepts into scalable, production-ready AI systems
Collaborate with cross-functional engineering and research teams to integrate ML models into real-world applications
Document methodologies, experimental findings, and technical solutions
Contribute to technical innovation initiatives and advanced AI research activities

Required Qualifications
Strong PhD research background in Machine Learning, Deep Learning, Artificial Intelligence, Computer Vision, Data Science, or related areas
Strong programming experience with Python and C++
Hands-on experience with PyTorch, TensorFlow, Keras, Scikit-learn, or similar ML frameworks
Strong understanding of Machine Learning, Deep Learning, Neural Networks, and AI algorithms
Experience developing and training advanced deep learning models and architectures
Solid mathematical foundation in linear algebra, probability, statistics, optimization, and applied machine learning
Experience working with Linux environments, Git, Docker, and modern development workflows
Demonstrated research experience through publications, thesis work, academic research projects, or equivalent research contributions
Strong ability to independently research, prototype, and deploy AI solutions

Preferred Qualifications
Publications in leading AI, Machine Learning, or Computer Science conferences/journals
Experience transitioning AI/ML models from research environments into production systems
Experience with CUDA, GPU acceleration, distributed computing, or high-performance computing
Experience handling large-scale, real-world datasets

This role is ideal for candidates passionate about applying advanced AI research, machine learning, and deep learning techniques to solve challenging real-world problems.