H-1B Visa Physical Scientist Jobs
Physical Scientist jobs at H-1B visa sponsoring employers span atmospheric research, geophysics, materials science, and federal contract labs. The role qualifies as a specialty occupation under H-1B rules, requiring at least a bachelor's degree in physics, chemistry, or a directly related discipline. Status is granted for up to three years, extendable to six.
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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 883+ H-1B Visa Physical Scientist Jobs
Sign up for free to unlock all listings, filter by visa type, and get alerts for new H-1B Visa Physical Scientist Jobs.
Get Access To All JobsTips for Finding H-1B Visa Sponsorship as a Physical Scientist
Align your degree to SOC codes
Physical Scientist roles map to multiple SOC codes depending on specialization. Pull the O*NET profile for your subfield before applying so your degree field and job duties match what the employer lists in the LCA, reducing RFE risk on specialty occupation grounds.
Check prevailing wages by worksite location
Your employer must certify the offered wage meets the prevailing wage for your specific worksite county, not the company's headquarters. Use the OFLC Wage Search to verify wage levels for your SOC code before comparing offers across different metro areas.
Target federal contractor and lab employers
Federal agencies and national laboratories operating under government contracts routinely sponsor H-1B Physical Scientists. These employers file cap-exempt petitions through affiliated nonprofits, which means no cap selection exposure and year-round filing windows regardless of when you receive your offer.
Find sponsors through Migrate Mate
Search Migrate Mate to identify employers with verified H-1B LCA filing history for Physical Scientist roles. Focusing on companies with an established filing track record in your specialization reduces the time between offer and petition submission significantly.
Secure a new LCA before switching worksites
If your employer reassigns you to a different worksite after your petition is approved, they must file a new certified LCA for that location before you begin working there. Confirm this process with your employer's HR team when negotiating any relocation or project assignment changes.
Request premium processing for cap-subject petitions
USCIS offers premium processing that provides a decision within 15 business days. For Physical Scientist roles tied to time-sensitive research contracts or grant start dates, requesting premium processing protects your project timeline and gives your employer certainty before onboarding.
H-1B Visa Physical Scientist: Frequently Asked Questions
Does a Physical Scientist role qualify as an H-1B specialty occupation?
Yes. Physical Scientist positions typically require at least a bachelor's degree in physics, chemistry, geoscience, atmospheric science, or a directly related discipline, which meets the specialty occupation standard. The employer documents the degree requirement in the Labor Condition Application and I-129 petition, and the specific subfield of your degree should correspond directly to the duties described in the job offer.
Which industries sponsor H-1B visas for Physical Scientists most consistently?
Federal contract research organizations, national laboratories, environmental consulting firms, defense contractors, and energy companies are consistent H-1B sponsors for Physical Scientists. Academic institutions also sponsor heavily, particularly for research-focused roles. Migrate Mate lists employers with verified LCA filing history in this occupation, so you can target your search toward organizations with an established sponsorship track record in your specialization.
How does the H-1B LCA process work for Physical Scientist positions?
Your employer files the Labor Condition Application with DOL before submitting the I-129 petition to USCIS. The LCA certifies that the offered wage meets the prevailing wage for your SOC code at your specific worksite location, and that hiring you won't adversely affect similarly employed U.S. workers. DOL typically certifies LCAs within seven business days. A separate certified LCA is required for each worksite where you'll perform work.
Can I transfer my H-1B to a new employer mid-status?
Yes, H-1B portability lets you start working for a new employer once they file a non-frivolous I-129 petition on your behalf, before USCIS approves it, as long as you've been in lawful H-1B status for at least 180 days. The new employer must file a fresh LCA certified for your new worksite and role duties, and your status period resets based on the new petition's validity dates, up to the six-year maximum.
What documentation strengthens an H-1B petition for a Physical Scientist?
Official transcripts confirming your degree in a directly related scientific field are foundational. If your specialty is narrow, such as geophysics or materials characterization, include peer-reviewed publications, professional licenses, or project documentation that ties your credentials to the specific SOC subcode the employer uses. If your degree title doesn't map cleanly to the job duties, a credentials evaluation from a USCIS-recognized evaluator and expert opinion letter from a subject-matter authority can address specialty occupation questions before an RFE is issued.