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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 are popular job titles related to Phd Vision Science jobs in Nevada?

For Phd Vision Science jobs in Nevada, the most frequently searched job titles are:

What job categories do people searching Phd Vision Science jobs in Nevada look for?

The top searched job categories for Phd Vision Science jobs in Nevada are:

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

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

Phd Vision Science jobs near you
Infographic showing various Phd Vision Science job openings in Nevada as of August 2026, with employment types broken down into 1% As Needed, 82% Full Time, 12% Part Time, and 5% Contract. Highlights an 94% Physical, 1% Hybrid, and 5% Remote job distribution.

Staff Applied Scientist Document Vision

Relativity

Las Vegas, NV • On-site

Other

Posted 22 days ago

Job description

Posting Type

Remote/Hybrid

Job Overview

The Work
Every legal matter is its own experiment. An attorney arrives with a theory of the case; the evidence arrives as hundreds of thousands of documents, sometimes millions, that no one has read and no model has seen. Somewhere in the cross product of the two are the answers that decide lawsuits, investigations, and livelihoods. Finding them quickly and defensibly, with the integrity and credibility attorneys can rely on, is the problem we own. We solve it creatively and rigorously.
Relativity is a data-centered, AI-native legal technology company, and Applied Science builds the AI inside Relativity aiR. We launched aiR in 2023 and have now run commercial generative AI in the legal domain for more than three years, powering work that includes the largest investigations in the world. Our systems are distinguished by the data they operate over (more than 93 petabytes) and the work they have done: over 190 million AI review decisions, backed by more than 1 billion generative sub-analyses in 2026 alone. The team is as distinctive as the data: legal experts, all former litigators, work directly inside Applied Science.
At Relativity, our mission is to Organize data. Discover the truth. Act on it. The Applied Science team serves this mission by building bold and ambitious AI systems. We are curious, dedicated, and humble. We understand complexity, uphold rigor, and measure relentlessly. We build and ship with pace. Above all, we are interdisciplinary collaborators and team players.
We're looking for a Staff Applied Scientist to take on our hardest problems in document vision and set standards that reach beyond a single team.

Job Description and Requirements

Capable and Reliable

Two requests can look nearly identical and be worlds apart. "See if you can find me an example of this" needs a capable system: it finds the example or it doesn't. "Conduct a reasonable search for any and all documents responsive to this request" is a different kind of promise. Its answer spans a corpus no one will ever read end-to-end. So the system's process, as much as its output, has to earn the trust of the professionals who rely on it.

That property is reliability. It decomposes into consistency, robustness, calibration, and safety: systems that behave tomorrow the way they did today, degrade predictably under stress, know how confident they should be, and check their own work. Before aiR returns an analysis, it validates its citations and runs internal consistency checks; when a check fails, it refuses to answer. It has refused more than a million times so far in 2026, and we count every one as a success: an error caught before it reached a user.

You'll build for both, and help define the standard for how.

The Focus: Document Vision

This role anchors our document-vision work: teaching systems to read evidence the way legal professionals do. Real matters arrive as scanned pages, photographs, tables, handwriting, stamps, and broken layouts, at the scale of millions of documents. You'll own the science of multimodal document understanding across aiR, from vision-language modeling to the evaluation standards that make visual evidence usable and defensible.

What You'll Do

  • Take on the hardest, most ambiguous problems in the portfolio and produce clarity: a well-specified approach, an evaluation that settles the question, a system that ships.
  • Set standards that reach beyond your team: evaluation methods, modeling patterns, and quality bars adopted by scientists you've never worked with.
  • Own readiness for flagship AI systems, from problem framing through efficacy studies and production monitoring, in partnership with engineering.
  • Multiply the team through deep review and mentorship of senior and lead scientists.
  • Advise Applied Science leadership on where the science is going and where we should invest.

What You Bring

  • A master's or PhD in computer science or another quantitative discipline (or equivalent professional experience), and at least 6 years of applied AI/ML experience.
  • Years of production AI/ML behind you: systems you specified, shipped, and operated at scale, in partnership with the engineers who run them.
  • Expert judgment about AI systems: you've built them, measured them, and formed views of their limits that hold up under challenge.
  • Scientific rigor other people borrow: you supervise the data understanding of teams beyond your own, your evaluations become the template, and your error analyses end debates.
  • Software-engineering judgment trusted across teams, and the programming skill to credibly prototype what you propose.
  • An ownership mindset that extends across the organization.

Nice to Have

  • Experience with vision-language or document-understanding models (layout analysis, OCR-adjacent pipelines, table and figure extraction) in production.
  • An interest in legal technology and the justice system.
  • Experience developing information retrieval systems.
  • Experience developing agentic harnesses.
  • Experience building reliable AI systems at scale.

Why Relativity Applied Science

This is the place where your curiosity, dedication, and talent will build products that power the pursuit of justice around the world.

Relativity is committed to competitive, fair, and equitable compensation practices.

This position is eligible for total compensation which includes a competitive base salary, an annual performance bonus, and long-term incentives.

The expected salary range for this role is between following values:

$197,000 and $295,000

The final offered salary will be based on several factors, including but not limited to the candidate's depth of experience, skill set, qualifications, and internal pay equity. Hiring at the top end of the range would not be typical, to allow for future meaningful salary growth in this position.

Required Skills:

Algorithms, Computer Vision, Data Analysis, Data Science, Deep Learning, Machine Learning (ML), Natural Language, Natural Language Processing (NLP), Python (Programming Language), Scientific Research

Apply