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Cern Physics Jobs (NOW HIRING)

University of Colorado

Postdoctoral Associate

Boulder, CO · On-site

$67K - $74K/yr

... for physics beyond the standard model. Experience or interest in firmware and/or machine learning is highly desirable. Primary locations for the position are Boulder or CERN, and is negotiable ...

Causal Labs

Deployment Strategist

San Francisco, CA · On-site

$120 - $190/hr

Our founding team has built and deployed AI against the physical world in robotics, drug discovery, and particle physics at institutions like DeepMind, Waymo, Cruise, Insitro, Nabla Bio, and CERN.

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Cern Physics information

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$39K

$46.9K

$52.5K

How much do cern physics jobs pay per year?

As of Sep 5, 2026, the average yearly pay for cern physics in the United States is $46,902.00, according to ZipRecruiter salary data. Most workers in this role earn between $43,500.00 and $50,500.00 per year, depending on experience, location, and employer.

What is the difference between Cern Physics vs Particle Physicist?

AspectCern PhysicsParticle Physicist
Required CredentialsAdvanced degrees in physics, often PhD, with specialization in high-energy physicsSimilar; PhD in physics or related field, with focus on particle research
Work EnvironmentResearch facilities like CERN, laboratories, large-scale experimentsResearch labs, universities, CERN, or other particle physics institutions
Industry UsagePrimarily in high-energy physics research, large international collaborationsAcademic, research institutions, and industry roles related to particle physics

In summary, Cern Physics refers to the field or research conducted at CERN involving high-energy particle experiments, while a Particle Physicist is a professional working within that field, often conducting experiments, analyzing data, and contributing to scientific discoveries in particle physics.

Does CERN hire physicists?

CERN hires physicists for research roles related to particle physics, engineering, and technical support. Candidates typically need advanced degrees in physics or related fields and relevant research experience. Employment opportunities include research positions, technical roles, and internships at CERN's facilities.
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Cities with the most Cern Physics job openings:

What states have the most Cern Physics jobs?

States with the most job openings for Cern Physics jobs include:

What job categories do people searching Cern Physics jobs look for?

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Cern Physics jobs near you
Infographic showing various Cern Physics job openings in the United States as of August 2026, with employment types broken down into 100% Full Time. Highlights an 100% In-person job distribution, with an average salary of $46,902 per year, or $22.5 per hour.

Member of Technical Staff - Training Infrastructure

Causal Labs

San Francisco, CA • On-site

Full-time

Re-posted 15 days ago

Job description

Our mission is general causal intelligence; AI that is capable of (1) predicting the future and (2) identifying the actions to alter it.
To achieve this breakthrough, we are building a Large Physics foundation Model (LPM) because physical systems, unlike text or images, are governed by verifiable cause and effect. We believe that scaling on physics will enable an understanding of causality required to predict and control physical systems, starting with weather.
Our founding team has built and deployed AI against the physical world in robotics, drug discovery, and particle physics at institutions like DeepMind, Waymo, Cruise, Insitro, Nabla Bio, and CERN.
We look for infrastructure engineers who are excited to tackle unsolved problems. Training an LPM means scaling novel architectures over multimodal physical data - a problem where the playbooks from language and vision only partially apply. Your mission is to make large-scale training fast, efficient, and reliable, so that every GPU cycle accelerates research progress.
Responsibilities
  • Design, implement, and optimize distributed training systems that scale across thousands of GPUs
  • Research and test parallelization strategies and numerical precision trade-offs across model scales, including for architectures that don't map cleanly onto existing LLM training stacks
  • Analyze, profile, and debug low-level GPU operations to maximize throughput and hardware utilization
  • Build reusable frameworks for checkpointing, fault tolerance, and reproducibility that stay robust under rapid research iteration
  • Collaborate with researchers to bring novel model architectures from prototype to full scale
  • Stay up-to-date on research to bring new ideas to work

What we're looking for
We value a relentless approach to problem-solving, rapid execution, and the ability to quickly learn in unfamiliar domains.
  • Demonstrated proficiency with distributed training frameworks and techniques (e.g. FSDP, DeepSpeed, Megatron, Pytorch, JAX/XLA) to train large foundation models
  • Strong grasp of state-of-the-art techniques for optimizing training workloads: parallelism strategies, memory optimization, mixed precision, communication overlap
  • Ability to profile and debug performance in complex codebases, from framework internals down to kernels and collectives
  • Deep understanding of deep learning frameworks (e.g. PyTorch, JAX) and their underlying system architectures
  • Bonus: contributions to open-source ML infrastructure (e.g. PyTorch, Megatron-LM, DeepSpeed, XLA)

Apply