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Mathematical Logic Phd Jobs in Texas (NOW HIRING)

Apple

Formal Verification - AI/ML Engineer

Austin, TX · On-site

$134K/yr

Background in formal methods, mathematical logic, or a strong mathematical foundation - whether ... MS or PhD in Computer Science, Electrical Engineering, Mathematics, or a related field - though ...

Apple Inc.

Formal Verification - AI/ML Engineer

Austin, TX · On-site

$120 - $160/hr

Background in formal methods, mathematical logic, or a strong mathematical foundation -- whether ... MS or PhD in Computer Science, Electrical Engineering, Mathematics, or a related field -- though ...

Apple

Formal Verification - AI/ML Engineer

Austin, TX

$184K - $324K/yr

Background in formal methods, mathematical logic, or a strong mathematical foundation - whether ... MS or PhD in Computer Science, Electrical Engineering, Mathematics, or a related field - though ...

Apple

Formal Verification - AI/ML Engineer

Austin, TX

$184K - $324K/yr

Background in formal methods, mathematical logic, or a strong mathematical foundation - whether ... MS or PhD in Computer Science, Electrical Engineering, Mathematics, or a related field - though ...

micro1 AI

Senior Scientific Reviewer - Physics

Irving, TX · On-site +1

$80 - $150/hr

Critically evaluate and review physics solutions, mathematical derivations, and theoretical ... PhD in physics and an active record of independent research within a specialized subfield (e.g ...

micro1 AI

AI Training Specialist - Physics

Killeen, TX · On-site +1

$80 - $150/hr

Critically evaluate and review physics solutions, mathematical derivations, and theoretical ... PhD in physics and an active record of independent research within a specialized subfield (e.g ...

micro1 AI

Senior Scientific Reviewer - Physics

Plano, TX · On-site +1

$80 - $150/hr

Critically evaluate and review physics solutions, mathematical derivations, and theoretical ... PhD in physics and an active record of independent research within a specialized subfield (e.g ...

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Mathematical Logic Phd information

What is a Mathematical Logic PhD?

A Mathematical Logic PhD is a doctoral degree focused on the study of formal systems, reasoning, and the foundations of mathematics. Students in this program research topics such as set theory, model theory, recursion theory, and proof theory. Graduates often pursue careers in academia, research, or industry roles that require advanced logical reasoning and mathematical skills. The program typically involves coursework, comprehensive exams, and original research culminating in a dissertation.

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

To thrive as a Mathematical Logic PhD, you need advanced knowledge of mathematical logic, formal systems, set theory, and proof techniques, typically supported by a doctoral degree in mathematics or a related field. Proficiency with mathematical software (such as LaTeX, Coq, or Mathematica) and experience with academic research tools are highly valuable. Strong analytical thinking, perseverance, and clear written and verbal communication skills help you excel in both independent research and collaborative academic environments. These competencies are crucial for advancing theoretical understanding, producing publishable research, and contributing to the broader mathematical community.

What are the typical research and collaboration opportunities available to someone with a PhD in Mathematical Logic?

A PhD in Mathematical Logic opens doors to research positions in academia, technology companies, and research institutes, where collaboration is key. You may work as part of interdisciplinary teams with computer scientists, mathematicians, and philosophers on projects like formal verification, artificial intelligence, or foundations of mathematics. Challenges often include communicating complex ideas to those outside your specialty and balancing independent research with collaborative projects. These roles frequently provide opportunities to publish, attend conferences, and mentor students, fostering both personal growth and professional networking.

What is the difference between Mathematical Logic Phd vs Data Scientist?

AspectMathematical Logic PhdData Scientist
Required CredentialsPhD in Mathematics or Logic, strong analytical skillsBachelor's or Master's in Data Science, Statistics, or related fields
Work EnvironmentAcademic, research institutions, or specialized think tanksCorporate, tech companies, or consulting firms
Industry UsageResearch, academia, theoretical developmentData analysis, machine learning, business insights
Common Search/ComparisonMathematical Logic Phd vs Data Scientist

The Mathematical Logic Phd typically focuses on theoretical research and academic roles requiring advanced mathematical and logical expertise. In contrast, a Data Scientist applies statistical and computational skills to analyze data and solve practical business problems. While both roles require strong analytical skills, their work environments and industry applications differ significantly.

What are popular job titles related to Mathematical Logic Phd jobs in Texas?

For Mathematical Logic Phd jobs in Texas, the most frequently searched job titles are:

What job categories do people searching Mathematical Logic Phd jobs in Texas look for?

The top searched job categories for Mathematical Logic Phd jobs in Texas are:

What cities in Texas are hiring for Mathematical Logic Phd jobs?

Cities in Texas with the most Mathematical Logic Phd job openings:

Mathematical Logic Phd jobs near you

Formal Verification - AI/ML Engineer

Apple

Austin, TX • On-site

$134K/yr

Full-time

Re-posted 25 days ago

Apple rating

8.1

Company rating: 8.1 out of 10

Based on 678 frontline employees who took The Breakroom Quiz

7th of 30 rated technology retailers

Job description

Apple's Hardware Technologies Formal Verification team is seeking an AI/ML Engineer to work at the intersection of Artificial Intelligence and Formal Verification. In this role, you will explore, prototype, and build AI-powered systems - with a focus on Large Language Models - to augment and transform how formal verification is performed on Apple Silicon.
You will work closely with formal verification engineers, design engineers, and EDA tool developers to identify high-impact opportunities and deliver practical, domain-specific AI applications.
Description
You will be responsible for:
Building domain-specific AI applications that leverage LLMs and other ML techniques to accelerate formal verification workflows - from specification interpretation to property generation, proof debugging, and beyond.
Developing and fine-tuning LLM-based systems tailored to hardware verification tasks, including retrieval-augmented generation (RAG) pipelines, agentic tool-use frameworks, and domain-adapted models.
Collaborating with formal verification engineers to deeply understand FV methodologies, pain points, and opportunities where AI can meaningfully improve productivity, quality, and coverage.
Prototyping novel AI-driven approaches for tasks such as automatic SVA property synthesis, natural-language-to-formal-specification translation, proof strategy recommendation, and intelligent counterexample analysis.
Evaluating and integrating emerging AI/ML research into practical, production-quality tools and workflows used by the FV team.
Establishing best practices and infrastructure for AI application development within the FV organization.
Minimum Qualifications
A minimum of a bachelor's degree in relevant field and a minimum of 10 years of relevant industry experience.
Preferred Qualifications
Strong hands-on experience building AI/ML applications, particularly those leveraging Large Language Models (LLMs) - including prompt engineering, fine-tuning, RAG architectures, agentic systems, or LLM-based tool chains.
Demonstrated ability to take AI capabilities from prototype to production - you have shipped or deployed AI-powered tools or applications, not just trained models.
Proficiency in Python and modern ML/AI frameworks and tooling (e.g., PyTorch, LangChain, LlamaIndex, Hugging Face, or similar).
Background in formal methods, mathematical logic, or a strong mathematical foundation - whether through academic training (e.g., formal methods, type theory, automated reasoning, mathematical logic) or applied experience. You don't need to be an FV expert, but a quantitative and rigorous mindset is essential.
Genuine interest in domain-specific AI applications - you are excited about going deep into a specialized engineering domain rather than building general-purpose AI products.
Software engineering best practices - version control, testing, API design, and building maintainable, collaborative codebases.
Excellent communication and interpersonal skills - you will work across disciplines with FV engineers, design engineers, and tooling teams.
Self-directed and comfortable with ambiguity - you will need to identify opportunities, propose solutions, and drive them forward.
Experience working on or contributing to LLM tooling, frameworks, or infrastructure (e.g., inference engines, model serving, evaluation harnesses).
Prior exposure to hardware design or verification concepts (RTL, SystemVerilog, assertions, EDA tools).
Familiarity with formal methods, SAT/SMT solvers, model checking, or theorem proving.
Experience with code generation or analysis tasks using LLMs.
MS or PhD in Computer Science, Electrical Engineering, Mathematics, or a related field - though exceptional industry experience is equally valued.

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Hours and flexibility

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About Apple

Sourced by ZipRecruiter

Imagine what you could do here! At Apple, new ideas have a way of becoming extraordinary products, services, and customer experiences very quickly. Bring passion and dedication to your job and there's no telling what you could accomplish. Dynamic, intelligent people and inspiring, innovative technologies are the norm here. The people who work here have reinvented entire industries with all Apple Hardware products. The same real passion for innovation that goes into our products also applies to our practices strengthening our dedication to leave the world better than we found it.

Industry

Computer and electronic product manufacturing

Company size

10,000+ Employees

Headquarters location

Cupertino, CA, US

Year founded

1976

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