ZipRecruiter

Log In

2

Remote Computational Materials Science Jobs in New York

Arcadis

Computational Designer

New York, NY · On-site +1

$22.50 - $27.25/hr

... materials to support projects Build quality relationships with team members and across the ... Science, Software Engineering, Hardware Engineering, or related fields (Master's Degree preferred ...

OXMAN

Senior Software Engineer

New York, NY · On-site +1

$134K - $176K/yr

Working across disciplines--from architecture and ecology to computation and materials science--we ... Collaborate with computational ecologists, designers, and researchers to translate models, methods ...

next page

Showing results 1-20

All JobsComputational Materials Science JobsRemote Computational Materials Science JobsRemote Computational Materials Science Jobs in New York

Remote Computational Materials Science information

What is remote computational materials science?

Remote computational materials science involves using computer simulations and modeling techniques to study and design materials, all while working from a remote location rather than in a physical lab. Researchers in this field use software tools to predict the properties and behaviors of materials at the atomic or molecular level, which can accelerate the discovery of new materials for applications in energy, electronics, and manufacturing. Remote computational materials scientists commonly collaborate with teams online, analyze data, and run simulations on high-performance computing systems accessible via the internet.

What are some common challenges faced when working remotely in computational materials science, and how can they be addressed?

Remote computational materials scientists often encounter challenges such as coordinating with interdisciplinary teams across different time zones and ensuring efficient access to high-performance computing resources. Clear communication through regular virtual meetings and collaborative platforms helps maintain project alignment. Additionally, staying organized with version control systems and thorough documentation is essential for seamless teamwork. Being proactive about addressing technical issues, such as software compatibility or data transfer limitations, also ensures productivity.

What are the key skills and qualifications needed to thrive as a remote computational materials scientist, and why are they important?

To thrive as a Remote Computational Materials Scientist, you need a strong background in materials science, physics, or chemistry, often with a PhD or advanced degree, and expertise in computational modeling. Familiarity with simulation software like VASP, Quantum ESPRESSO, or LAMMPS, as well as proficiency in programming languages such as Python or Fortran, is typically required. Excellent problem-solving skills, self-motivation, and clear written communication are crucial for collaborating remotely and conveying complex results. These competencies enable effective independent research, accurate data analysis, and seamless teamwork in a virtual scientific environment.

What is the difference between Remote Computational Materials Science vs Remote Materials Data Analyst?

AspectRemote Computational Materials ScienceRemote Materials Data Analyst
Required CredentialsAdvanced degrees in materials science, physics, or chemistry; experience with computational modelingBachelor's or master's in data science, materials science, or related fields; proficiency in data analysis tools
Work EnvironmentResearch-focused, using simulation software and programmingData processing, visualization, and reporting using analytics platforms
Employer & Industry UsageResearch institutions, R&D departments in manufacturing, tech companiesManufacturers, consulting firms, research labs analyzing material data

Remote Computational Materials Science involves simulating and modeling materials at the atomic or molecular level, requiring programming and scientific expertise. In contrast, Remote Materials Data Analysts focus on analyzing existing material data to inform decisions, emphasizing data skills. Both roles are essential in materials research but differ in their core activities and skill sets.

What are the most commonly searched types of Computational Materials Science jobs in New York?

The most popular types of Computational Materials Science jobs in New York are:

What are popular job titles related to Remote Computational Materials Science jobs in New York?

For Remote Computational Materials Science jobs in New York, the most frequently searched job titles are:

What job categories do people searching Remote Computational Materials Science jobs in New York look for?

The top searched job categories for Remote Computational Materials Science jobs in New York are:

What cities in New York are hiring for Remote Computational Materials Science jobs?

Cities in New York with the most Remote Computational Materials Science job openings:

Remote Computational Materials Science jobs near you

Computational Physics Expert - Remote

YO AI Labs

New York, NY • Remote

Full-time

Posted 9 days ago

Job description

Job Title: Computational Physics AI Expert

Role Type: Contractor
Location: Remote

Job Overview

We are seeking experienced Computational Physics Experts to contribute their technical expertise to a project focused on advancing next-generation AI systems. In this role, you will provide real-world examples of computational physics problem-solving and demonstrate how modern AI coding agents can be applied to sophisticated technical workflows.

The ideal candidate is a STEM professional with hands-on experience using AI coding agents such as Codex, Claude Science, Claude Code, and Claude Cowork as active tools in computational and technical work.

No prior experience in AI training is required—your computational physics expertise, technical judgment, and ability to apply agentic tools to complex problems are what matter most.

Scope of Work
  • Provide detailed, real-world walkthroughs of computational physics problem-solving using AI coding agents in complex technical environments.
  • Demonstrate the use of Codex, Claude Science, Claude Code, and Claude Cowork for advanced technical workflows.
  • Document how AI agents are used for tasks such as navigating large codebases, debugging complex issues, developing sophisticated features, and automating multi-step workflows.
  • Clearly describe the approaches, technical decisions, methodologies, and agent-generated sequences used to solve computational problems.
  • Evaluate workflows in which AI agents contribute to architectural changes, codebase modifications, debugging, and ambiguous computational challenges.
  • Develop high-quality technical examples, evaluations, and feedback to support AI training and model improvement.
  • Analyze the accuracy, effectiveness, and limitations of AI-generated solutions in computational physics contexts.
  • Communicate technical findings and insights through clear written and verbal documentation.
  • Collaborate with project stakeholders to refine technical examples, workflows, and evaluation criteria.
Required Skills
  • Computational Physics
  • Python
  • AI Coding Agents
  • Codex
  • Claude Science
  • Claude Code
  • Claude Cowork
  • Debugging
  • Technical Documentation
  • Architectural Change Management
  • Problem-Solving
  • Technical Communication
Preferred Qualifications
  • Advanced hands-on experience in computational physics, scientific computing, numerical methods, simulation, or related technical fields.
  • Demonstrated experience using Codex, Claude Science, Claude Code, and Claude Cowork in real-world technical workflows.
  • Current or recent experience as a STEM professional applying AI coding agents to complex technical problems beyond basic coding assistance.
  • Strong Python programming skills and experience working with scientific or computational codebases.
  • Ability to clearly explain complex, end-to-end technical solutions and the role AI agents played throughout the workflow.
  • Experience generating and evaluating agent-driven sequences and multi-step workflows, rather than relying primarily on conversational AI interactions.
  • Experience debugging complex systems and identifying subtle technical issues with the assistance of AI coding agents.
  • Familiarity with architectural change management, refactoring, and development within large or complex codebases.
  • Strong written and verbal communication skills, with the ability to produce detailed and technically accurate documentation.
  • Strong analytical thinking and the ability to evaluate AI-generated technical solutions critically.