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Phd Vision Science Jobs in Georgia (NOW HIRING)

PhD degree in Computer Science, Engineering, Applied Mathematics or related STEM field * Experience ... This package includes employer subsidized Medical, Dental, Vision, and Life Insurance; Short-Term ...

PhD degree in Computer Science, Engineering, Applied Mathematics or related STEM field * Experience ... This package includes employer subsidized Medical, Dental, Vision, and Life Insurance; Short-Term ...

PhD degree in Computer Science, Engineering, Applied Mathematics or related STEM field * Experience ... This package includes employer subsidized Medical, Dental, Vision, and Life Insurance; Short-Term ...

Education level preferred, MD/PhD or Master's in public health, biological sciences, epidemiology ... vision insurance, flexible spending accounts, short and long term disability, company paid life ...

PhD degree in Computer Science, Engineering, Applied Mathematics or related STEM field * Experience ... This package includes employer subsidized Medical, Dental, Vision, and Life Insurance; Short-Term ...

PhD degree in Computer Science, Engineering, Applied Mathematics or related STEM field * Experience ... This package includes employer subsidized Medical, Dental, Vision, and Life Insurance; Short-Term ...

New

PhD degree in Computer Science, Engineering, Applied Mathematics or related STEM field * Experience ... This package includes employer subsidized Medical, Dental, Vision, and Life Insurance; Short-Term ...

New

Principal Data Scientist

Atlanta, GA · On-site +1

$165K - $249K/yr

Whatyou'llown Strategy and vision: * Define the technical vision and strategy fornew data driven ... science, Statistics, Mathematics, Engineering, or related field (PhD preferred) * 7+ years in ML ...

Define best practices and develop clear vision for data analysis and model productionalization ... PhD in a quantitative field (Computer Science, Math, Statistics, etc.) * 6+ years of experience in ...

Showing results 41-60

Phd Vision Science information

What is a PhD in Vision Science?

A PhD in Vision Science is an advanced research degree focused on the study of visual systems, including how vision works and how visual disorders are diagnosed and treated. Students in these programs explore topics such as ocular anatomy, visual perception, neuroscience, and eye diseases. Graduates often pursue careers in academia, clinical research, optometry, or the development of new vision technologies. The program typically involves both coursework and original research leading to a dissertation.

What are the key skills and qualifications needed to thrive as a PhD in Vision Science?

To thrive as a PhD in Vision Science, you need advanced knowledge of ocular anatomy, physiology, optics, research methodology, and often experience in clinical or laboratory settings. Proficiency with data analysis tools (such as MATLAB or Python), imaging systems, and scientific publishing platforms is typically required. Strong critical thinking, problem-solving, and effective communication skills distinguish successful professionals in this field. These skills are essential for conducting high-quality research, driving innovation, and effectively sharing findings with both scientific and clinical communities.

What are some typical research collaborations for someone in a PhD Vision Science role?

PhD Vision Science professionals often work closely with interdisciplinary teams that include optometrists, ophthalmologists, neuroscientists, and engineers. Collaborations frequently involve designing and conducting experiments, sharing data, and co-authoring publications to advance understanding of visual processes and eye diseases. These partnerships can extend to industry settings—such as developing vision correction technologies or diagnostic tools—offering diverse opportunities to broaden your research impact and professional network.

What is the difference between Phd Vision Science vs Optometrist?

AspectPhd Vision ScienceOptometrist
Required CredentialsPhD in Vision Science or related fieldDoctor of Optometry (OD) license
Work EnvironmentResearch labs, academia, industryClinical settings, private practices, clinics
Industry UsageResearch, product development, academiaPatient eye care, vision testing, prescriptions

While both roles focus on vision, a Phd Vision Science primarily involves research and development in vision-related fields, whereas an Optometrist provides clinical eye care and prescriptions. The PhD is research-oriented, often in labs or academia, while optometrists work directly with patients in clinical settings.

What can I do with a Phd vision science degree?

A PhD in vision science prepares individuals for research, academia, and advanced roles in vision-related industries such as ophthalmology, optometry, and biomedical device development. Graduates often work as university professors, research scientists, or in industry roles involving vision technology, requiring skills in data analysis, experimental design, and scientific communication.

What cities in Georgia are hiring for Phd Vision Science jobs?

Cities in Georgia with the most Phd Vision Science job openings:

Infographic showing various Phd Vision Science job openings in Georgia as of August 2026, with employment types broken down into 1% As Needed, 71% Full Time, 15% Part Time, 10% Contract, and 3% Nights. Highlights an 96% Physical, 1% Hybrid, and 3% Remote job distribution.

Data Scientist II - Scientific AI

McKinsey & Company

Atlanta, GA • On-site

Full-time

Re-posted 22 days ago


McKinsey & Company rating

8.5

Company rating: 8.5 out of 10

Based on 22 frontline employees who took The Breakroom Quiz

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Job description

Do you want to do work that matters, alongside supportive leaders who will help you grow faster than you ever thought possible? Are you a creative problem-solver who is energized by challenges? You've come to the right place.
YOUR IMPACT
Your work will be split between developing new internal knowledge, building AI and machine learning models & pipelines, supporting client discussions, prototype development, and deploying directly with client delivery teams.
You will bring distinctive statistical, machine learning, and AI competency to complex client problems. With your expertise in advanced mathematics, statistics, and/or machine learning, you will help build and shape McKinsey's scientific AI offering.
You will play a pivotal role in the creation/dissemination of cutting-edge knowledge and proprietary assets. You will work in a multi-disciplinary team and build the firm's reputation in your area of expertise. You will ensure statistical validity and outputs of analytics, AI/ML models and translate results for senior stakeholders.
You will write optimized code to advance our Data Science Toolbox and codify analytical methodologies for future deployment. You will be working in one of our offices in North America in our Life Sciences practice.
You will work with cutting edge AI teams on research and development topics across our life sciences, global energy and materials (GEM), and advanced industries (AI) practices, serving as a data scientist in a technology development and delivery capacity.
You will be on McKinsey's global Scientific AI team helping to answer industry questions related to how AI can be used for therapeutics, chemicals & materials (including small molecules, proteins, mRNA, polymers, etc.).
You will support the manager of data science on the development of data science and analytics roadmap of assets across cell-level initiatives. You will deliver distinctive capabilities, models, and insights through your work with client teams and clients.
YOUR GROWTH
Driving lasting impact and building long-term capabilities with our clients is not easy work. You are the kind of person who thrives in a high performance/high reward culture - doing hard things, picking yourself up when you stumble, and having the resilience to try another way forward.
In return for your drive, determination, and curiosity, we'll provide the resources, mentorship, and opportunities you need to become a stronger leader faster than you ever thought possible. Your colleagues-at all levels-will invest deeply in your development, just as much as they invest in delivering exceptional results for clients. Every day, you'll receive apprenticeship, coaching, and exposure that will accelerate your growth in ways you won't find anywhere else.
When you join us, you will have:
  • Continuous learning: Our learning and apprenticeship culture, backed by structured programs, is all about helping you grow while creating an environment where feedback is clear, actionable, and focused on your development. The real magic happens when you take the input from others to heart and embrace the fast-paced learning experience, owning your journey.
  • A voice that matters: From day one, we value your ideas and contributions. You'll make a tangible impact by offering innovative ideas and practical solutions. We not only encourage diverse perspectives, but they are critical in driving us toward the best possible outcomes.
  • Global community: With colleagues across 65+ countries and over 100 different nationalities, our firm's diversity fuels creativity and helps us come up with the best solutions for our clients. Plus, you'll have the opportunity to learn from exceptional colleagues with diverse backgrounds and experiences.
  • World-class benefits: On top of a competitive salary (based on your location, experience, and skills), we provide a comprehensive benefits package to enable holistic well-being for you and your family.

YOUR QUALIFICATIONS AND SKILLS
  • Master's or PhD degree
  • 2+ years of relevant experience in statistics, mathematics, computer science, or equivalent experience with experience in research
  • Proven experience applying machine learning techniques to solve business problems
  • Proven experience in translating technical methods to non-technical stakeholders
  • Strong programming experience in python (R, Python, C++ optional) and the relevant analytics libraries (e.g., pandas, numpy, matplotlib, scikit-learn, statsmodels, pymc, pytorch/tf/keras, langchain)
  • Experience with version control (GitHub)
  • ML experience with causality, Bayesian statistics & optimization, survival analysis, design of experiments, longitudinal analysis, surrogate models, transformers, Knowledge Graphs, Agents, Graph NNs, Deep Learning, computer vision
  • Ability to write production code and object-oriented programming

Please review the additional requirements regarding essential job functions of McKinsey colleagues.
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