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Lidar Python Phd Jobs (NOW HIRING)

Avride

Machine Learning Engineer Internship

Austin, TX · On-site

RGB-Only 3D Perception & RGB-LiDAR Fusion * Applied Research Ownership: Lead a scoped research ... Build out the backend infrastructure using Python to map and search Avride's massive library of ...

Nvidia

OR · On-site

... lidar data, multiview batching, large-scene rendering, and memory-sensitive training paths ... Translate high-impact Python, NumPy, or PyTorch bottlenecks into efficient CUDA/C++ or PyTorch ...

Qualcomm

Automotive Software Test, Staff

San Diego, CA · On-site

$53 - $68.50/hr

... Python a must). • Strong analytical, problem-solving and debugging skills. • Experience with ... PhD in Engineering, Information Systems, Computer Science, or related field and 2+ years of ...

Anduril Industries

AI Sorcerer

Costa Mesa, CA

$131K - $173K/yr

Strong programming skills in Python or other core languages (Java, Go etc) * PhD or Master's degree ... Experience in multi-modal sensor data processing (e.g., cameras, LiDAR, radar). * Familiarity with ...

Mach9 Robotics Inc

ML Engineer

San Francisco, CA · On-site

We build models to extract 3D object and line features from dense LiDAR point clouds and imagery ... Master's or PhD in Machine Learning, Computer Vision, Computer Science, or a related field, or ...

TerraClear

Senior Robotics Engineer

Issaquah, WA

$150/hr

MS or PhD in CS, EE, ME or a related field, or equivalent experience * Strong C++, Python skills ... Experience integrating a wide range of sensing hardware, including LIDAR, cameras, other range ...

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How much do lidar python phd jobs pay per year?

As of Jun 7, 2026, the average yearly pay for lidar python phd in the United States is $139,971.00, according to ZipRecruiter salary data. Most workers in this role earn between $110,500.00 and $164,500.00 per year, depending on experience, location, and employer.

What are some typical challenges faced when working as a Lidar Python PhD in a research or industry setting?

As a Lidar Python PhD, you may encounter challenges such as handling large-scale, high-dimensional point cloud data, ensuring efficient data processing pipelines, and optimizing algorithms for real-time performance. Collaborating with multidisciplinary teams—such as hardware engineers, data scientists, and software developers—is common, and clear communication is key when translating research findings into deployable solutions. Additionally, staying current with advances in both Lidar technology and Python-based machine learning tools is essential for driving innovation and maintaining project relevance.

What is the difference between Lidar Python Phd vs Lidar Data Analyst?

AspectLidar Python PhdLidar Data Analyst
Required CredentialsPhD in relevant field, Python expertiseBachelor's or Master's in related field, some Python skills
Work EnvironmentResearch labs, academia, R&D departmentsIndustry, surveying firms, engineering teams
Industry UsageAdvanced research, algorithm development, academic publishingData processing, visualization, reporting

The Lidar Python Phd typically focuses on advanced research, developing algorithms, and academic contributions, requiring a PhD and strong Python skills. In contrast, a Lidar Data Analyst applies existing tools to process and interpret lidar data in industry settings, often with a bachelor's or master's degree. Both roles involve lidar data and Python, but differ in scope, environment, and expertise level.

What does a Lidar Python PhD professional do?

A Lidar Python PhD professional specializes in analyzing and processing data collected by Lidar (Light Detection and Ranging) systems, typically using the Python programming language. They develop algorithms to interpret 3D spatial data, automate data processing workflows, and contribute to research in fields like geospatial analysis, autonomous vehicles, and environmental monitoring. Their work often involves advanced computational techniques, data visualization, and collaboration with interdisciplinary teams to turn raw Lidar data into actionable insights.

What are the key skills and qualifications needed to thrive as a Lidar Python PhD, and why are they important?

To thrive as a Lidar Python PhD, you need expertise in lidar data processing, advanced knowledge of Python programming, and a doctoral degree in a relevant field such as computer science, remote sensing, or geospatial science. Familiarity with libraries like NumPy, SciPy, and open-source lidar tools (e.g., PDAL, LASpy), as well as experience with data analysis platforms and machine learning frameworks, are typically required. Strong problem-solving abilities, attention to detail, and effective collaboration and communication skills set candidates apart in this role. These competencies are crucial for accurately analyzing complex lidar datasets, developing innovative solutions, and contributing to interdisciplinary research and development projects.

Physicist with Security Clearance

Alaire Technologies, Inc

Alexandria, VA

Other

Posted 26 days ago

Job description

Alaire Technologies is Hiring! Join Alaire to support our customers in pushing the limits on advanced sensors and processing technologies to give the Navy and Marines the edge they need in the battlespace.  Location: Alexandria VA // Washington D.C. Position summary We are seeking a motivated PhD-level Physicist to develop and validate advanced sensor signal- and image-processing algorithms with emphasis on atmospheric propagation effects, radiative transfer, and performance prediction in maritime and littoral environments.

The scientist will lead algorithm development for electro-optical/infrared and active sensors, perform modeling and measurement-based characterization of atmospheric turbulence, scattering, and aerosol effects, and deliver software and analysis that enable operational sensor performance for Navy systems. Key responsibilities Research, design, implement, and validate sensor processing algorithms (detection, tracking, classification, change detection) for EO/IR and active sensors accounting for atmospheric propagation and platform motion. Develop and maintain atmospheric propagation and radiative-transfer models (theory and numerical implementation) and integrate them into system-level performance models.

Analyze field and laboratory sensor datasets; calibrate/validate models against measurements and perform uncertainty quantification. Collaborate with systems engineers, experimental teams, and program offices to translate algorithms into deliverable code, provide test plans, and support at-sea/field experimentation. Publish peer-reviewed papers, prepare technical reports, and present findings to Navy stakeholders.

Required qualifications PhD in Physics, Applied Physics, Electrical Engineering, Atmospheric Science, or closely related field. Demonstrated research/engineering experience in sensor algorithms (statistical detection, tracking, machine learning for sensors) and atmospheric propagation (turbulence, scattering, radiative transfer). Strong programming skills (Python, MATLAB, C/C++, or equivalent), experience with numerical modeling and data analysis.

Experience with sensor calibration, experimental design, and full life-cycle algorithm validation. Preferred Prior experience with maritime or aerospace sensor programs, lidar/radar/EO test campaigns, or working in a government/DoD laboratory. Familiarity with high-performance computing, model-based systems engineering (MBSE), or ML frameworks applied to remote sensing.

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