Zymtronix Catalytic Systems Inc
Lead Software Scientist for Interactive AI Systems in Materials Science
Zymtronix Catalytic Systems Inc, Northeast Ithaca, New York, United States
Lead Software Scientist for Interactive AI Systems in Materials Science
The Role
Cornell Research & Innovation seeks a highly experienced researcher–engineer to conceive, lead, and build an interactive, LLM-based AI system for materials science research. This is a unique position that sits at the intersection of artificial intelligence, materials science, human–computer interaction, and research leadership.
Unlike a traditional software engineering role, this position requires deep scientific engagement, technical leadership, and hands‑on system building, from early design through a fully usable, deployed research tool. The successful candidate will embed directly within materials science research environments to ensure that the resulting system is scientifically powerful, intuitive to use, and tightly aligned with real research workflows.
This position will serve as a key contributor to the U.S. NSF‑sponsored Artificial Intelligence Materials Institute (AI‑MI). AI‑MI will accelerate and transform the discovery of new materials to be used in sustainable energy, advanced electronics, environmental stewardship and quantum technologies by integrating human scientific expertise with AI methods. Researchers from Cornell University make up the leadership team, joined by researchers from Princeton University, the City University of New York, and Boston University. The goal of NSF AI‑MI is to harness the rising tide of materials data, using AI to enable scientists to develop new materials based on prediction, while also developing trustworthy AI and deepening our fundamental understanding of AI.
Core responsibilities of this position include:
Scientific AI System Design and Leadership
Lead the end‑to‑end design and development of an interactive, LLM‑based AI system tailored to materials science research.
Define the system’s technical and scientific vision, balancing cutting‑edge AI methods with usability, robustness, and long‑term sustainability.
Make architectural decisions spanning model integration, data representations, interaction paradigms, and deployment strategies.
Translate open‑ended scientific goals into concrete system requirements and deliverables.
Integration of Research into a Production‑Quality System
Work closely with PhD students and postdoctoral researchers in materials science, physics, and computer science to incorporate latest research results—including new models, representations, and scientific insights—into the evolving system.
Bridge the gap between research prototypes and a cohesive, production‑quality platform, ensuring reliability, reproducibility, and extensibility.
Evaluate when and how new research ideas should be integrated, refined, or redesigned to meet real‑world research needs.
Human‑Centered Design for Scientific Workflows
Embed within a materials science research lab to observe, understand, and analyze how researchers actually work—including how they explore data, generate hypotheses, run experiments, and interpret results.
Lead the design of interaction models, interfaces, and workflows that align with these practices.
Ensure the system is usable, discoverable, and adoptable by materials scientists—not just technically impressive.
Continuously assess and refine the system based on researcher feedback, usage patterns, and evolving scientific practices.
Collaboration and Mentorship
Serve as a technical and scientific leader for interdisciplinary teams of PhD students and postdocs.
Coordinate contributions across AI, materials science, and physics researchers, aligning individual research efforts with the system’s broader goals.
Mentor junior researchers on system design, scientific software development, and translating research ideas into usable tools.
Foster a collaborative environment that values both scientific innovation and practical impact.
Project and Research Leadership
Lead complex, multi‑year projects involving multiple stakeholders, disciplines, and evolving research directions.
Set milestones, prioritize work, and manage technical risk in a research‑driven environment.
Communicate progress and design decisions clearly to both technical and non‑technical audiences.
Contribute to long‑term strategy around scientific AI infrastructure and tooling within the institute.
Essential Qualifications
PhD in computer science, computational science, engineering, materials science, physics or a closely related field
Experience designing and building complex AI or data‑driven systems
Demonstrated proficiency in at least one major programming language commonly used in AI/ML and scientific computing (e.g., Python), including use of modern software engineering practices (version control, testing, packaging, CI/CD), with experience making architectural decisions for shared or production‑quality systems
Experience supporting others’ code development (e.g., code reviews, pair programming, mentoring, building reusable templates or libraries), and providing technical leadership across interdisciplinary research teams
Experience developing and maintaining web‑based tools or portals, including use of common web frameworks and APIs, particularly for interactive or research‑facing AI systems
Familiarity with AI/ML tools and workflows (e.g., PyTorch, TensorFlow, JAX, scikit‑learn) and with data management for research (e.g., large datasets, metadata, reproducible experiments), including experience integrating new research models or methods into stable, usable platforms
Strong interpersonal and communication skills, with demonstrated ability to work effectively with stakeholders, including students, faculty, and staff, and to translate open‑ended research goals into concrete technical designs and deliverables
Demonstrated success in mentorship of junior researchers and engineers
Experience working in a research‑intensive environment with demonstrated collaboration across AI and domain science teams
Experience with scientific computing and numerical libraries; database design and management (SQL/NoSQL), data catalogs, or research data repositories; and cloud platforms and containerization (e.g., AWS, GCP, Docker, Kubernetes), including deployment and maintenance of shared or long‑lived research infrastructure
Experience building research software portals or platforms for collaborative use, particularly systems that integrate AI/ML models, data, and interactive user workflows
Experience with tools such as GitHub/GitLab, project management platforms, and documentation systems (e.g., Sphinx, ReadTheDocs, Jupyter), with a track record of establishing or improving team‑wide development practices
Compensation
The anticipated salary range for this research associate position is $150,000–$160,000. The initial appointment is for three years and can be renewed based on satisfactory performance and availability of funds.
How To Apply
Cover letter
Curriculum vitae
Names and contact information for three references (letters of recommendation will be requested later in the process)
Additional materials may be requested during the interview process.
About Us
Cornell University is an innovative Ivy League university and a great place to work. Cornell's inclusive community of scholars, students and staff impart an uncommon sense of larger purpose and contribute creative ideas to further the university's mission of teaching, discovery and engagement. Cornell provides great benefits that include comprehensive health care options, generous retirement contributions, educational benefits (Employee Degree, Tuition Aid, Cornell Children’s Tuition Assistance Programs), access to wellness programs, and employee discounts with local and national retail brands. Our time away from work provisions include 22 days of vacation and 13 holidays, including winter break from December 25th through January 1st. Cornell has been nationally recognized as an award‑winning workplace for our health, wellbeing, and sustainability initiatives. For more information, follow the link: Benefits at Cornell.
Pay Ranges
Prior relevant work or industry experience.
Education level to the extent education is relevant to the position.
Academic Discipline
Unique applicable skills.
Employment Assistance
For general questions about the position or the application process, please contact the Recruiter listed in the job posting or email mycareer@cornell.edu.
If you require an accommodation for a disability in order to complete an employment application or to participate in the recruiting process, you are encouraged to contact Cornell Office of Civil Rights at voice (607) 255-2242, or email at accommodations@cornell.edu.
Applicants that do not have internet access are encouraged to visit your local library, or local Department of Labor. You may also request an appointment to use a dedicated workstation in the Office of Talent Attraction and Recruitment, at the Ithaca campus, by emailing mycareer@cornell.edu.
Notice to Applicants
Please read the required Notice to Applicants statement by
clicking here . This notice contains important information about applying for a position at Cornell as well as some of your rights and responsibilities as an applicant.
EEO Statement
Cornell welcomes students, faculty, and staff with diverse backgrounds from across the globe to pursue world‑class education and career opportunities, to further the founding principle of “... any person ... any study.” No person shall be denied employment on the basis of any legally protected status or subjected to prohibited discrimination involving, but not limited to, such factors as race, ethnic or national origin, citizenship and immigration status, color, sex, pregnancy or pregnancy‑related conditions, age, creed, religion, actual or perceived disability (including persons associated with such a person), arrest and/or conviction record, military or veteran status, sexual orientation, gender expression and/or identity, an individual’s genetic information, domestic violence victim status, familial status, marital status, or any other characteristic protected by applicable federal, state, or local law.
Cornell University embraces diversity in its workforce and seeks job candidates who will contribute to a climate that supports students, faculty, and staff of all identities and backgrounds. We hire based on merit, and encourage people from historically underrepresented and/or marginalized identities to apply. Consistent with federal law, Cornell engages in affirmative action in employment for qualified protected veterans as defined in the Vietnam Era Veterans’ Readjustment Assistance Act (VEVRAA) and qualified individuals with disabilities under Section 503 of the Rehabilitation Act. We also recognize a lawful preference in employment practices for Native Americans living on or near Indian reservations in accordance with applicable law.
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Cornell Research & Innovation seeks a highly experienced researcher–engineer to conceive, lead, and build an interactive, LLM-based AI system for materials science research. This is a unique position that sits at the intersection of artificial intelligence, materials science, human–computer interaction, and research leadership.
Unlike a traditional software engineering role, this position requires deep scientific engagement, technical leadership, and hands‑on system building, from early design through a fully usable, deployed research tool. The successful candidate will embed directly within materials science research environments to ensure that the resulting system is scientifically powerful, intuitive to use, and tightly aligned with real research workflows.
This position will serve as a key contributor to the U.S. NSF‑sponsored Artificial Intelligence Materials Institute (AI‑MI). AI‑MI will accelerate and transform the discovery of new materials to be used in sustainable energy, advanced electronics, environmental stewardship and quantum technologies by integrating human scientific expertise with AI methods. Researchers from Cornell University make up the leadership team, joined by researchers from Princeton University, the City University of New York, and Boston University. The goal of NSF AI‑MI is to harness the rising tide of materials data, using AI to enable scientists to develop new materials based on prediction, while also developing trustworthy AI and deepening our fundamental understanding of AI.
Core responsibilities of this position include:
Scientific AI System Design and Leadership
Lead the end‑to‑end design and development of an interactive, LLM‑based AI system tailored to materials science research.
Define the system’s technical and scientific vision, balancing cutting‑edge AI methods with usability, robustness, and long‑term sustainability.
Make architectural decisions spanning model integration, data representations, interaction paradigms, and deployment strategies.
Translate open‑ended scientific goals into concrete system requirements and deliverables.
Integration of Research into a Production‑Quality System
Work closely with PhD students and postdoctoral researchers in materials science, physics, and computer science to incorporate latest research results—including new models, representations, and scientific insights—into the evolving system.
Bridge the gap between research prototypes and a cohesive, production‑quality platform, ensuring reliability, reproducibility, and extensibility.
Evaluate when and how new research ideas should be integrated, refined, or redesigned to meet real‑world research needs.
Human‑Centered Design for Scientific Workflows
Embed within a materials science research lab to observe, understand, and analyze how researchers actually work—including how they explore data, generate hypotheses, run experiments, and interpret results.
Lead the design of interaction models, interfaces, and workflows that align with these practices.
Ensure the system is usable, discoverable, and adoptable by materials scientists—not just technically impressive.
Continuously assess and refine the system based on researcher feedback, usage patterns, and evolving scientific practices.
Collaboration and Mentorship
Serve as a technical and scientific leader for interdisciplinary teams of PhD students and postdocs.
Coordinate contributions across AI, materials science, and physics researchers, aligning individual research efforts with the system’s broader goals.
Mentor junior researchers on system design, scientific software development, and translating research ideas into usable tools.
Foster a collaborative environment that values both scientific innovation and practical impact.
Project and Research Leadership
Lead complex, multi‑year projects involving multiple stakeholders, disciplines, and evolving research directions.
Set milestones, prioritize work, and manage technical risk in a research‑driven environment.
Communicate progress and design decisions clearly to both technical and non‑technical audiences.
Contribute to long‑term strategy around scientific AI infrastructure and tooling within the institute.
Essential Qualifications
PhD in computer science, computational science, engineering, materials science, physics or a closely related field
Experience designing and building complex AI or data‑driven systems
Demonstrated proficiency in at least one major programming language commonly used in AI/ML and scientific computing (e.g., Python), including use of modern software engineering practices (version control, testing, packaging, CI/CD), with experience making architectural decisions for shared or production‑quality systems
Experience supporting others’ code development (e.g., code reviews, pair programming, mentoring, building reusable templates or libraries), and providing technical leadership across interdisciplinary research teams
Experience developing and maintaining web‑based tools or portals, including use of common web frameworks and APIs, particularly for interactive or research‑facing AI systems
Familiarity with AI/ML tools and workflows (e.g., PyTorch, TensorFlow, JAX, scikit‑learn) and with data management for research (e.g., large datasets, metadata, reproducible experiments), including experience integrating new research models or methods into stable, usable platforms
Strong interpersonal and communication skills, with demonstrated ability to work effectively with stakeholders, including students, faculty, and staff, and to translate open‑ended research goals into concrete technical designs and deliverables
Demonstrated success in mentorship of junior researchers and engineers
Experience working in a research‑intensive environment with demonstrated collaboration across AI and domain science teams
Experience with scientific computing and numerical libraries; database design and management (SQL/NoSQL), data catalogs, or research data repositories; and cloud platforms and containerization (e.g., AWS, GCP, Docker, Kubernetes), including deployment and maintenance of shared or long‑lived research infrastructure
Experience building research software portals or platforms for collaborative use, particularly systems that integrate AI/ML models, data, and interactive user workflows
Experience with tools such as GitHub/GitLab, project management platforms, and documentation systems (e.g., Sphinx, ReadTheDocs, Jupyter), with a track record of establishing or improving team‑wide development practices
Compensation
The anticipated salary range for this research associate position is $150,000–$160,000. The initial appointment is for three years and can be renewed based on satisfactory performance and availability of funds.
How To Apply
Cover letter
Curriculum vitae
Names and contact information for three references (letters of recommendation will be requested later in the process)
Additional materials may be requested during the interview process.
About Us
Cornell University is an innovative Ivy League university and a great place to work. Cornell's inclusive community of scholars, students and staff impart an uncommon sense of larger purpose and contribute creative ideas to further the university's mission of teaching, discovery and engagement. Cornell provides great benefits that include comprehensive health care options, generous retirement contributions, educational benefits (Employee Degree, Tuition Aid, Cornell Children’s Tuition Assistance Programs), access to wellness programs, and employee discounts with local and national retail brands. Our time away from work provisions include 22 days of vacation and 13 holidays, including winter break from December 25th through January 1st. Cornell has been nationally recognized as an award‑winning workplace for our health, wellbeing, and sustainability initiatives. For more information, follow the link: Benefits at Cornell.
Pay Ranges
Prior relevant work or industry experience.
Education level to the extent education is relevant to the position.
Academic Discipline
Unique applicable skills.
Employment Assistance
For general questions about the position or the application process, please contact the Recruiter listed in the job posting or email mycareer@cornell.edu.
If you require an accommodation for a disability in order to complete an employment application or to participate in the recruiting process, you are encouraged to contact Cornell Office of Civil Rights at voice (607) 255-2242, or email at accommodations@cornell.edu.
Applicants that do not have internet access are encouraged to visit your local library, or local Department of Labor. You may also request an appointment to use a dedicated workstation in the Office of Talent Attraction and Recruitment, at the Ithaca campus, by emailing mycareer@cornell.edu.
Notice to Applicants
Please read the required Notice to Applicants statement by
clicking here . This notice contains important information about applying for a position at Cornell as well as some of your rights and responsibilities as an applicant.
EEO Statement
Cornell welcomes students, faculty, and staff with diverse backgrounds from across the globe to pursue world‑class education and career opportunities, to further the founding principle of “... any person ... any study.” No person shall be denied employment on the basis of any legally protected status or subjected to prohibited discrimination involving, but not limited to, such factors as race, ethnic or national origin, citizenship and immigration status, color, sex, pregnancy or pregnancy‑related conditions, age, creed, religion, actual or perceived disability (including persons associated with such a person), arrest and/or conviction record, military or veteran status, sexual orientation, gender expression and/or identity, an individual’s genetic information, domestic violence victim status, familial status, marital status, or any other characteristic protected by applicable federal, state, or local law.
Cornell University embraces diversity in its workforce and seeks job candidates who will contribute to a climate that supports students, faculty, and staff of all identities and backgrounds. We hire based on merit, and encourage people from historically underrepresented and/or marginalized identities to apply. Consistent with federal law, Cornell engages in affirmative action in employment for qualified protected veterans as defined in the Vietnam Era Veterans’ Readjustment Assistance Act (VEVRAA) and qualified individuals with disabilities under Section 503 of the Rehabilitation Act. We also recognize a lawful preference in employment practices for Native Americans living on or near Indian reservations in accordance with applicable law.
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