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Job Summary
We are seeking a highly motivated and experienced Research Scientist to join Prof. Jiyoung Kim’s laboratory. The successful candidate will take a leading role in conducting and managing advanced research projects focused on semiconductor devices, fabrication processes, and characterization. This position requires a proactive individual who can drive research initiatives including experiments, data generation\-organization, presentations and reports, particularly, proposal writing as well. The research scientist is required to publish high impact journal/conference papers, manage laboratory operations/maintenance/upgrades, and provide mentorship/teaching to junior researchers as well.
Minimum Education and Experience
Master’s degree in a field directly related to specified research area and two (2\) years of directly applicable experience conducting research related to the specified field of study.
Preferred Education and Experience
Ph.D. in a field related to semiconductor device process integration (such as Materials Science and Engineering, Electrical Engineering, Chemistry, or Physics), with a minimum of 10 peer\-reviewed journal and conference papers published as the first author within the last 3 years.
Other Qualifications
To the extent this position requires the holder to research, work on, or have access to critical infrastructure as defined in Section 117\.001(2\) of the Texas Business and Commerce Code, the ability to maintain the security or integrity of the critical infrastructure is a minimum qualification to be hired and to continue to be employed in the position.
Essential Duties and Responsibilities
Research Leadership: Independently lead, execute, and manage research projects related to semiconductor devices, processing, and characterization. The candidate must successfully operate various vacuum systems, such as ALD, ALE, CVD, PVD, and characterization. And the candidate should have extensive and intensive knowledge on semiconductor device electrical performance and characterization. The candidate should also have extensive hands\-on experience in cleanroom fabrication and semiconductor metrology tools as well as semiconductor electrical characterization.
Data Management \& Reporting: Organize research data systematically and prepare comprehensive technical reports summarizing project progress and outcomes.
Academic Publishing: Write and submit high\-quality research articles for peer\-reviewed journals and academic conferences.
Grant Writing: Actively participate in drafting and developing research proposals to secure external funding.
Laboratory Management: Take a primary role in overseeing lab operations, ensuring safety compliance, managing equipment, and maintaining a productive research environment.
Mentorship: Provide direct and indirect guidance, training, and mentorship to graduate and undergraduate students within the laboratory.
Physical Demands and Working Conditions Physical Activities Working Conditions Additional Information
*Internal candidates may receive preference*
*A remote work schedule is not available for this position.*
What We Can Offer
UT Dallas is an Equal Opportunity Employer with an employee\-friendly and supportive work environment. Our comprehensive compensation and benefits package that is effective as of your hire date includes:
- Competitive Salary
- Tuition Benefits
- Internal Training
- BCBS PPO Medical insurance – 100% paid for full\-time employees
- PPO and DHMO Dental Insurance Plan – PPO plans include ortho benefits
- Long and short\-term disability
- TRS Retirement Plan – defined benefit plan offering lifetime annuity upon retirement
- Voluntary Retirement Plan Options – additional savings opportunities with Tax\-Sheltered Annuity Plans and Deferred Compensation Plans
- Dental/Vision/AD\&D
- Paid time off
- Paid Holidays
- Paid Winter Break
- Fertility Benefits
All UT Dallas employees have access to various professional development opportunities, including a membership to Academic Impressions, LinkedIn Learning, and UT Dallas Bright Leaders Program.
Visit https://hr.utdallas.edu/employees/benefits/ for more information.
If you are looking for a rewarding career opportunity with great benefits? Look no further! Join our team!
Special Instructions Summary
Please include a list of the ten most important published papers as the first author that you have written.
Important Message
1\) All employees serve as a representative of the University and are expected to display respect, civility, professional courtesy, consideration of others and discretion in all interactions with members of the UT Dallas community and the general public.
2\) The University of Texas at Dallas is committed to providing an educational, living, and working environment that is welcoming, respectful, and inclusive of all members of the university community. UT Dallas does not discriminate on the basis of race, color, religion, sex (including pregnancy), sexual orientation, gender identity, gender expression, age, national origin, disability, genetic information, or veteran status in its services, programs, activities, employment, and education, including in admission and enrollment. The University *is committed to providing access, equal opportunity, and reasonable accommodation* for individuals with disabilities. *To request reasonable accommodation in the employment application and interview process, contact the* *ADA* *Coordinator.* For inquiries regarding nondiscrimination policies, contact the Title IX Coordinator**.
Role Details
About This Role
Research Scientists push the boundaries of what AI can do. They design experiments, develop novel architectures, publish papers, and translate research breakthroughs into production capabilities. This is where the fundamental advances happen, from attention mechanisms to diffusion models to reasoning chains.
The work is intellectually demanding and often ambiguous. You might spend months on an approach that doesn't pan out. The best research scientists combine deep mathematical intuition with engineering pragmatism. They know when to go deep on theory and when to run experiments. They read papers voraciously and can spot incremental contributions from genuine breakthroughs.
Across the 3,708 AI roles we're tracking, Research Scientist positions make up 3% of the market. At University of Texas at Dallas, this role fits into their broader AI and engineering organization.
Research Scientist roles are concentrated at major AI labs (OpenAI, Anthropic, Google DeepMind, Meta FAIR) and well-funded AI startups. The competition is intense. PhD is effectively required for most positions, and publication track record matters. Compensation is among the highest in AI, reflecting both the scarcity of talent and the strategic importance of research breakthroughs.
What the Work Looks Like
A typical week includes: reading and discussing recent papers with your team, designing and running experiments on multi-GPU clusters, analyzing results and iterating on hypotheses, writing up findings for internal review or publication, and collaborating with engineering teams to productionize promising results. The ratio of thinking to coding is higher than in engineering roles.
Research Scientist roles are concentrated at major AI labs (OpenAI, Anthropic, Google DeepMind, Meta FAIR) and well-funded AI startups. The competition is intense. PhD is effectively required for most positions, and publication track record matters. Compensation is among the highest in AI, reflecting both the scarcity of talent and the strategic importance of research breakthroughs.
Skills in Demand for This Role
PhD strongly preferred for most roles. Deep expertise in a specific area (NLP, computer vision, reinforcement learning, multimodal) is expected. PyTorch is the standard. Publication track record matters. Strong mathematical foundations in linear algebra, probability, optimization, and information theory are assumed.
Beyond the fundamentals, companies value experience with large-scale distributed training, novel architecture design, and the ability to bridge theory and practice. Understanding of current frontier topics (reasoning, multimodal, long-context, alignment) is essential. Code quality matters more than many researchers expect. Labs want researchers who can implement their ideas cleanly.
Strong research postings specify the research area, mention the team you'd join, and describe the problems they're working on. They often list recent publications from the team. Vague 'AI research' postings without specifics usually mean the company wants to sound impressive but doesn't have a real research agenda.
Compensation Benchmarks
Research Scientist roles pay a median of $222,200 based on 197 positions with disclosed compensation. Mid-level AI roles across all categories have a median of $200,000.
Across all AI roles, the market median is $217,500. Top-quartile compensation starts at $272,100. The 90th percentile reaches $325,000. For comparison, the highest-paying categories include AI Safety ($300,000) and Research Engineer ($280,000). By seniority level: Entry: $120,000; Mid: $200,000; Senior: $230,000; Director: $272,150; VP: $250,000.
University of Texas at Dallas AI Hiring
University of Texas at Dallas has 1 open AI role right now. They're hiring across Research Scientist. Based in Richardson, TX, US.
Location Context
Across all AI roles, 14% (508 positions) offer remote work, while 3,180 require on-site attendance. Top AI hiring metros: New York (1,045 roles, $220,000 median); San Francisco (810 roles, $277,088 median); Los Angeles (397 roles, $215,000 median).
Career Path
Common paths into Research Scientist roles include PhD Student, Research Engineer, Postdoc.
From here, career progression typically leads toward Research Lead, Distinguished Scientist, VP of Research.
The PhD is the entry point for most paths. Choose your advisor and research area carefully since they'll define your first industry position. Publish consistently, contribute to open-source projects in your area, and build relationships at conferences. Industry research offers better compensation and compute resources than academia, but the pressure to show product impact is real.
What to Expect in Interviews
Research interviews are multi-stage: a research talk (present your best paper), technical deep-dives on your methodology, and often a 'research proposal' exercise where you design an experiment to test a hypothesis. Coding rounds test implementation ability alongside theoretical knowledge. Be prepared to implement a paper from scratch and discuss the design choices the authors made. Strong candidates can critique papers constructively and identify gaps in experimental methodology.
When evaluating opportunities: Strong research postings specify the research area, mention the team you'd join, and describe the problems they're working on. They often list recent publications from the team. Vague 'AI research' postings without specifics usually mean the company wants to sound impressive but doesn't have a real research agenda.
AI Hiring Overview
The AI job market has 3,708 open positions tracked in our dataset. By seniority: 102 entry-level, 1,705 mid-level, 1,469 senior, and 432 leadership roles (Director, VP, C-Level). Remote roles make up 14% of the market (508 positions). The remaining 3,180 roles require on-site or hybrid attendance.
The market median for AI roles is $217,500. Top-quartile compensation starts at $272,100. The 90th percentile reaches $325,000. Highest-paying categories: AI Safety ($300,000 median, 21 roles); Research Engineer ($280,000 median, 147 roles); AI Architect ($254,798 median, 67 roles).
Research Scientist roles are concentrated at major AI labs (OpenAI, Anthropic, Google DeepMind, Meta FAIR) and well-funded AI startups. The competition is intense. PhD is effectively required for most positions, and publication track record matters. Compensation is among the highest in AI, reflecting both the scarcity of talent and the strategic importance of research breakthroughs.
The AI Job Market Today
The AI job market spans 3,708 open positions across 16 role categories. The largest categories by volume: AI/ML Engineer (2,605), Data Scientist (310), AI Software Engineer (259). These three account for the majority of open positions, though smaller categories often have higher per-role compensation because of specialized skill requirements.
The seniority mix tells a story about where AI teams are in their maturity. Entry-level roles (102) are outnumbered by mid-level (1,705) and senior (1,469) positions, reflecting that most companies are past the 'build a team from scratch' phase and need experienced engineers who can ship production systems. Leadership roles (Director, VP, C-Level) total 432 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 14% of all AI roles (508 positions), with 3,180 requiring on-site or hybrid attendance. The remote share has stabilized after the post-pandemic correction. Senior and specialized roles (Research Scientist, ML Architect) are more likely to be remote-eligible than entry-level positions, partly because experienced hires have more negotiating power and partly because these roles require less hands-on mentorship.
AI compensation is structured in clear tiers. The market median sits at $217,500. Top-quartile roles start at $272,100, and the 90th percentile reaches $325,000. These figures include base salary with disclosed compensation. Total compensation (including equity, bonuses, and sign-on) runs 20-40% higher at companies that offer those components.
Category matters for compensation. AI Safety roles lead at $300,000 median, while Prompt Engineer roles sit at $140,000. The spread between highest and lowest-paying categories reflects the premium on specialized technical skills versus broader analytical roles.
The most in-demand skills across all AI postings: Python (1,890 postings), Aws (1,103 postings), Azure (877 postings), Rag (855 postings), Gcp (631 postings), Prompt Engineering (560 postings), Pytorch (545 postings), Claude (498 postings). Python dominates, appearing in the vast majority of role descriptions regardless of category. Cloud platform experience (AWS, GCP, Azure) is the second most common requirement. The newer entrants to the top skills list (RAG, vector databases, LLM APIs) reflect the shift from traditional ML toward generative AI applications.
Frequently Asked Questions
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