Physical Scientist Jobs in USA with Visa Sponsorship
Physical Scientist roles in atmospheric research, geophysics, and materials science regularly qualify as specialty occupations under the H-1B visa, making employer-sponsored visas a realistic path. Many positions sit inside universities, federal contractors, and national labs that file LCAs annually. A relevant graduate degree is typically the baseline credential employers need to file.
Find Physical Scientist JobsOverview
Showing 5 of 924+ Physical Scientist jobs
See all 924+ Physical Scientist Jobs
Sign up for free to unlock all listings, filter by visa type, and get alerts for new Physical Scientist roles.
Get Access To All JobsThe Position
A healthier future. It’s what drives us to innovate. To continuously advance science and ensure everyone has access to the healthcare they need today and for generations to come. Creating a world where we all have more time with the people we love. That’s what makes us Roche.
Advances in AI, data, and computational sciences are transforming drug discovery and development. Roche’s Research and Early Development organisations at Genentech (gRED) and Pharma (pRED) have demonstrated how these technologies accelerate R&D, leveraging data and novel computational models to drive impact. Seamless data sharing and access to models across gRED and pRED are essential to maximising these opportunities. The new Computational Sciences Center of Excellence (CoE) is a strategic, unified group whose goal is to harness the transformative power of data and Artificial Intelligence (AI) to assist our scientists in both pRED and gRED to deliver more innovative and transformative medicines for patients worldwide.
The Opportunity
At Genentech (gRED) and Roche (pRED), we’re applying Physical AI to solve one of humanity’s hardest challenges: building fully autonomous, self-healing laboratories for lights-out drug discovery.
Advances in AI, data, and computational sciences are transforming drug discovery and development. The Computational Sciences Center of Excellence (CoE) and the Data and Digital Catalyst (DDC) team are building the foundational platform for autonomous labs – turning state-of-the-art AI into real-world physical action to deliver life-saving medicines to patients faster than ever before.
As a Senior Physical AI & Robotics Scientist, you will be the hands-on technical lead and scientific architect bringing Physical AI to life – deploying 3D perception, multi-physics digital twins, edge vision, and closed-loop control onto state-of-the-art robotic hardware using cutting-edge stacks like NVIDIA Isaac, Omniverse, and Metropolis. If you are inspired by the challenge of bridging foundation models with complex real-world hardware to give robots the spatial awareness and resilience to autonomously solve problems on the lab floor, this is your opportunity to pioneer the next generation of autonomous laboratories at global scale.
In this role, you will:
- Develop 3D computer vision perception pipelines (point clouds, depth maps, pose estimation) and dynamic motion planning algorithms (ROS 2, MoveIt 2, cuMotion) to enable reliable arm manipulation, hand-eye calibration, grasping, and AMR navigation in dynamic workcells.
- Build multi-physics simulation environments (NVIDIA Isaac Sim/Lab, Newton Engine) to model robot-labware interactions, evaluate LLM-generated execution plans inside digital twins before deployment, and train policy recovery models.
- Apply system identification, domain randomization, and sim-to-real tuning to ensure simulation-trained control policies execute predictably on physical hardware.
- Fine-tune multimodal Vision AI models (VLMs, NVIDIA Cosmos) using synthetic failure datasets (Isaac Sim) for real-time detection of lab anomaly modes (spills, bubbles, dropped microplates, tilted lids, tip-pick misses).
- Optimize low-latency inference with TensorRT on NVIDIA Jetson (Thor/Orin) edge hardware, combining visual servoing and closed-loop feedback control so systems self-correct without halting master workflows.
- Harness OpenUSD scene graphs to represent workcell geometry and state, integrating synchronization services to link executable digital twins across heterogeneous hardware APIs (SiLA 2, gRPC, vendor SDKs).
Who You Are
Core Qualifications & Experience
- MS in Computer Science, Robotics, Electrical Engineering, Mechanical Engineering, or related technical field with 5+ years of experience, or a PhD with 2+ years of experience in deploying Physical AI or robotics solutions.
- Strong interest in translating physical AI capabilities into biological workflows and drug discovery pipelines.
- Passionate builder with a proven track record of taking real-world robotic manipulation and sim-to-real systems beyond demonstrations into sustained operation.
- Strong background in 3D computer vision, kinematics, motion planning (ROS 2, MoveIt 2, cuMotion), and modern machine learning frameworks (PyTorch) with strong C++/Python skills.
- Hands-on experience with robotics simulation and robot-learning frameworks (NVIDIA Isaac Sim/Lab, Newton, MuJoCo, Drake, Gazebo) and sim-to-real validation methods.
- Experience training or fine-tuning vision/multimodal models (VLMs, Cosmos) and optimizing neural networks with TensorRT for edge hardware (Jetson Thor/Orin).
- Proficiency with visual servoing, closed-loop controllers, and hardware API integration (gRPC, SiLA 2, vendor SDKs).
Preferred but not required
- Hands-on experience with OpenUSD scene graphs, custom USD schemas, or NVIDIA Omniverse workflows.
- Experience working with high-throughput lab automation hardware, manipulators, or liquid handlers (e.g., Hamilton, Tecan, Precise Automation, UR arms).
- Background in imitation learning, reinforcement learning, or robot foundation models for contact-rich manipulation and recovery.
- A public portfolio of real-world projects on GitHub/GitLab showcasing work in robotics, simulation, or physical AI.
Relocation benefits are NOT available for this opportunity.
The expected salary range for this position based on the primary location of San Francisco is $168,100 - 312,300 of hiring range. Actual pay will be determined based on experience, qualifications, geographic location, and other job-related factors permitted by law. A discretionary annual bonus may be available based on individual and Company performance. This position also qualifies for the benefits detailed at the link provided below.
Benefits
Genentech is an equal opportunity employer. It is our policy and practice to employ, promote, and otherwise treat any and all employees and applicants on the basis of merit, qualifications, and competence. The company's policy prohibits unlawful discrimination, including but not limited to, discrimination on the basis of Protected Veteran status, individuals with disabilities status, and consistent with all federal, state, or local laws.
If you have a disability and need an accommodation in relation to the online application process, please contact us by completing this form Accommodations for Applicants.
The Position
A healthier future. It’s what drives us to innovate. To continuously advance science and ensure everyone has access to the healthcare they need today and for generations to come. Creating a world where we all have more time with the people we love. That’s what makes us Roche.
Advances in AI, data, and computational sciences are transforming drug discovery and development. Roche’s Research and Early Development organisations at Genentech (gRED) and Pharma (pRED) have demonstrated how these technologies accelerate R&D, leveraging data and novel computational models to drive impact. Seamless data sharing and access to models across gRED and pRED are essential to maximising these opportunities. The new Computational Sciences Center of Excellence (CoE) is a strategic, unified group whose goal is to harness the transformative power of data and Artificial Intelligence (AI) to assist our scientists in both pRED and gRED to deliver more innovative and transformative medicines for patients worldwide.
The Opportunity
At Genentech (gRED) and Roche (pRED), we’re applying Physical AI to solve one of humanity’s hardest challenges: building fully autonomous, self-healing laboratories for lights-out drug discovery.
Advances in AI, data, and computational sciences are transforming drug discovery and development. The Computational Sciences Center of Excellence (CoE) and the Data and Digital Catalyst (DDC) team are building the foundational platform for autonomous labs – turning state-of-the-art AI into real-world physical action to deliver life-saving medicines to patients faster than ever before.
As a Senior Physical AI & Robotics Scientist, you will be the hands-on technical lead and scientific architect bringing Physical AI to life – deploying 3D perception, multi-physics digital twins, edge vision, and closed-loop control onto state-of-the-art robotic hardware using cutting-edge stacks like NVIDIA Isaac, Omniverse, and Metropolis. If you are inspired by the challenge of bridging foundation models with complex real-world hardware to give robots the spatial awareness and resilience to autonomously solve problems on the lab floor, this is your opportunity to pioneer the next generation of autonomous laboratories at global scale.
In this role, you will:
- Develop 3D computer vision perception pipelines (point clouds, depth maps, pose estimation) and dynamic motion planning algorithms (ROS 2, MoveIt 2, cuMotion) to enable reliable arm manipulation, hand-eye calibration, grasping, and AMR navigation in dynamic workcells.
- Build multi-physics simulation environments (NVIDIA Isaac Sim/Lab, Newton Engine) to model robot-labware interactions, evaluate LLM-generated execution plans inside digital twins before deployment, and train policy recovery models.
- Apply system identification, domain randomization, and sim-to-real tuning to ensure simulation-trained control policies execute predictably on physical hardware.
- Fine-tune multimodal Vision AI models (VLMs, NVIDIA Cosmos) using synthetic failure datasets (Isaac Sim) for real-time detection of lab anomaly modes (spills, bubbles, dropped microplates, tilted lids, tip-pick misses).
- Optimize low-latency inference with TensorRT on NVIDIA Jetson (Thor/Orin) edge hardware, combining visual servoing and closed-loop feedback control so systems self-correct without halting master workflows.
- Harness OpenUSD scene graphs to represent workcell geometry and state, integrating synchronization services to link executable digital twins across heterogeneous hardware APIs (SiLA 2, gRPC, vendor SDKs).
Who You Are
Core Qualifications & Experience
- MS in Computer Science, Robotics, Electrical Engineering, Mechanical Engineering, or related technical field with 5+ years of experience, or a PhD with 2+ years of experience in deploying Physical AI or robotics solutions.
- Strong interest in translating physical AI capabilities into biological workflows and drug discovery pipelines.
- Passionate builder with a proven track record of taking real-world robotic manipulation and sim-to-real systems beyond demonstrations into sustained operation.
- Strong background in 3D computer vision, kinematics, motion planning (ROS 2, MoveIt 2, cuMotion), and modern machine learning frameworks (PyTorch) with strong C++/Python skills.
- Hands-on experience with robotics simulation and robot-learning frameworks (NVIDIA Isaac Sim/Lab, Newton, MuJoCo, Drake, Gazebo) and sim-to-real validation methods.
- Experience training or fine-tuning vision/multimodal models (VLMs, Cosmos) and optimizing neural networks with TensorRT for edge hardware (Jetson Thor/Orin).
- Proficiency with visual servoing, closed-loop controllers, and hardware API integration (gRPC, SiLA 2, vendor SDKs).
Preferred but not required
- Hands-on experience with OpenUSD scene graphs, custom USD schemas, or NVIDIA Omniverse workflows.
- Experience working with high-throughput lab automation hardware, manipulators, or liquid handlers (e.g., Hamilton, Tecan, Precise Automation, UR arms).
- Background in imitation learning, reinforcement learning, or robot foundation models for contact-rich manipulation and recovery.
- A public portfolio of real-world projects on GitHub/GitLab showcasing work in robotics, simulation, or physical AI.
Relocation benefits are NOT available for this opportunity.
The expected salary range for this position based on the primary location of San Francisco is $168,100 - 312,300 of hiring range. Actual pay will be determined based on experience, qualifications, geographic location, and other job-related factors permitted by law. A discretionary annual bonus may be available based on individual and Company performance. This position also qualifies for the benefits detailed at the link provided below.
Benefits
Genentech is an equal opportunity employer. It is our policy and practice to employ, promote, and otherwise treat any and all employees and applicants on the basis of merit, qualifications, and competence. The company's policy prohibits unlawful discrimination, including but not limited to, discrimination on the basis of Protected Veteran status, individuals with disabilities status, and consistent with all federal, state, or local laws.
If you have a disability and need an accommodation in relation to the online application process, please contact us by completing this form Accommodations for Applicants.
See all 924+ Physical Scientist Jobs
Sign up for free to unlock all listings, filter by visa type, and get alerts for new Physical Scientist roles.
Get Access To All JobsTips for Finding Visa Sponsorship as a Physical Scientist
Align your degree field to your specialty
Physical Scientist is a broad title. Consular officers and USCIS scrutinize whether your specific degree field matches the role. A physics or geoscience degree supporting an atmospheric modeling position reads far stronger than a general science credential.
Target federal contractors and national labs
Federal agencies like DOE, NOAA, and NASA contract heavily with research organizations that file LCAs routinely. These employers have established sponsorship pipelines for Physical Scientist roles and experience navigating PERM for permanent residence cases.
Search verified sponsoring employers on Migrate Mate
Identifying which employers have active LCA filing history for Physical Scientist roles saves weeks of research. Use Migrate Mate to browse verified sponsoring employers by role and location before you apply.
Use OFLC Wage Search to anchor salary negotiations
Your employer must certify prevailing wage compliance on the LCA. Run an OFLC Wage Search for your specific worksite location and job zone before accepting an offer, so you can flag any wage-level mismatch early in the process.
Get your credentials evaluated before filing
If your degree is from outside the U.S., obtain a formal equivalency evaluation before the LCA is filed. A three-year bachelor's in physics from Australia or India can support H-1B eligibility, but only with a recognized credential evaluation on file.
Clarify publication and security clearance timelines with HR
Many Physical Scientist roles at research institutions require security clearances or publication approval processes that can delay your start date. Confirm whether your employer's I-129 filing timeline accounts for clearance processing before accepting an offer.
Frequently Asked Questions
Does a Physical Scientist role qualify as a specialty occupation for the H-1B?
Yes, in most cases. USCIS evaluates whether the role requires at least a bachelor's degree in a directly related field. Atmospheric scientist, geophysicist, and materials scientist positions typically satisfy that standard. Generalist research assistant roles framed broadly as 'physical scientist' can draw RFEs, so the job description should explicitly name the specialized sub-discipline and degree requirement.
What degree fields support a Physical Scientist sponsorship case?
Physics, atmospheric science, geophysics, geochemistry, oceanography, materials science, and related STEM disciplines all map cleanly to Physical Scientist roles. The closer the degree field matches the actual research specialty, the stronger the LCA and I-129 petition. A general science or interdisciplinary degree can work but typically requires additional documentation to establish the degree-to-role connection.
Which visa types are realistic for sponsored Physical Scientist positions?
The H-1B is the most common path for private-sector and contractor roles. University and nonprofit research positions may qualify for cap-exempt H-1B status, bypassing the annual lottery entirely. Canadian and Mexican nationals can use the TN visa under the scientist category listed in USMCA. Australian nationals can apply for the E-3 visa, which has no lottery and an annual cap that has never been exhausted.
How do I find Physical Scientist jobs with active visa sponsorship?
Migrate Mate lists employers with verified LCA filing history for Physical Scientist roles, so you can focus your search on organizations that have sponsored similar positions before. This is more reliable than filtering general job boards, where sponsorship willingness is often unstated or inconsistent.
Does a Physical Scientist role at a university avoid the H-1B lottery?
It can. Institutions of higher education and affiliated nonprofits are cap-exempt under USCIS rules, meaning their H-1B petitions are not subject to the annual 65,000 regular cap or the lottery. If you're hired directly by a university or a qualifying research organization attached to one, your employer can file an H-1B petition at any time of year without waiting for the lottery selection period.
What is the prevailing wage requirement for sponsored Physical Scientist jobs?
U.S. employers sponsoring a visa must pay at least the prevailing wage, which is what workers in the same role, area, and experience level typically earn. The Department of Labor sets this rate to make sure companies aren't hiring foreign workers simply because they'd accept lower pay than a U.S. worker. It varies by job title, location, and experience. You can look up current prevailing wage rates for any occupation and location using the OFLC Wage Search page.