לוח משרות דרושים מדעים מדוייקים בהרצליה, לחיפוש זה נמצאו 25 משרות

Define experimental and theoretical research strategies to characterize light-tissue interactions, optical penetration, and thermal/mechanical effects in biological media.
Design, build, and operate experimental lab setups to investigate photo-induced tissue damage (e.g., dermal and ocular tissue models), defining precise biological damage thresholds and exposure margins.
Serve as the team's foremost authority on laser safety, leading formal laser classification (e.g., IEC 60825, ANSI Z136, FDA CDRH) and product safety compliance.
Translate complex biological damage models and physical limits into actionable system-level specifications, hardware constraints, and operational safeguards.
Define and design system level solutions for safety compliance.
Develop and validate analytical and numerical simulation models (e.g., Monte Carlo light transport, thermal bio-heat equations) to predict tissue response and optical safety margins.
Analyze and report empirical findings clearly, enabling cross-functional engineering teams to make rigorous, risk-informed architecture decisions.
Partner with multidisciplinary teams across hardware, firmware, optics, and human factors to drive feasibility from concept to safe, viable product implementations.

Responsibilities
Lead the biological and physical risk assessment for novel optical concepts, pinpointing exposure limits, hazards, and mitigation pathways.
Conduct hands-on lab experiments combining lasers and biological tissue models to measure, observe, and quantify damage mechanisms under varied irradiation profiles.
Formulate and own the formal laser product classification strategy, defining engineering controls, interlocks, and compliance documentation.
Characterize system-level physical limits and optical delivery parameters (wavelength, pulse duration, fluence, beam profile) to maximize performance while strictly adhering to safety standards.
Author comprehensive safety reports, compliance dossiers, and technical whitepapers to support engineering choices and regulatory alignment.

We are looking for a Physics & Optical Simulation Software Engineer to build and scale our simulation platforms and data pipelines that power our physical modeling and sensor research. While the domain involves physics and optics, this is a software-first role: you will architect modular, high-throughput simulation systems that turn theoretical formulations into production-grade software tools. We value strong software engineering discipline, expertise in Python, and the intellectual agility to quickly master new scientific domains and innovate.

Responsibilities
Architect, build, and maintain robust, end-to-end simulation pipelines and scalable developer platforms.
Design modular, high-throughput simulation workflows and infrastructure in Python and modern scientific stacks.
Partner with physicists and optical engineers to translate physical models, wave-propagation algorithms, and numerical solvers into performant, clean software modules.
Optimize simulation frameworks for performance, scalability, data throughput, and maintainability.
Develop verification suites, benchmarking frameworks, and automated regression testing pipelines to validate simulation outputs against ground-truth and physical measurements.
Establish best practices for simulation software: modular packaging, version control, CI/CD, and technical documentation within a research-driven engineering environment.

We are seeking a creative and hands-on Deep Learning Research Engineer to drive model and architecture innovation across our sensing platforms. In this role, you will go beyond off-the-shelf models, exploring novel neural network designs, designing rigorous training and validation pipelines, and translating inventive concepts into clean, high-performance implementations. While our domain deals with physical data, this is an ML-first role: we are looking for a deep learning specialist with strong research intuition, expertise in PyTorch, and the drive to solve non-standard, real-world problems.

Responsibilities
Conceive, design, and implement novel neural network architectures tailored for complex physical sensing, reconstruction, and inverse problems.
Lead end-to-end hands-on research: data preparation, model formulation, training, hyperparameter exploration, and failure-mode analysis.
Build, train, and rigorously validate deep learning models using Python and PyTorch.
Formulate custom loss functions, regularization techniques, and inductive biases that capture domain-specific constraints.
Design comprehensive validation and benchmarking suites to stress-test model robustness, generalization, and scaling behavior.
Propose creative, non-conventional modeling ideas, stay abreast of state-of-the-art DL literature, and rapidly prototype proof-of-concepts.
Collaborate cross-functionally with physicists and optical software engineers to benchmark models against simulated and experimental lab datasets.

We are looking for a research scientist with an extraordinary theoretical background in machine learning and computational mathematics. This is a foundational theory role: we are seeking someone who truly understands how learning algorithms function from first principles, identifies computational and statistical barriers, and proves what is achievable under information-theoretic constraints.
While knowledge of privacy mechanisms (such as Differential Privacy) and cryptography is a strong advantage, the core priority is deep theoretical maturity in statistical learning, sample complexity, and optimization theory. You will bridge mathematical rigor with practical algorithmic innovation, shaping the next generation of our private machine learning.

Responsibilities
Conduct foundational theoretical research into the limits, bounds, and trade-offs of learning algorithms under privacy, computational, and statistical constraints.
Formulate and prove theoretical guarantees for machine learning models, analyzing sample complexity, generalization error, and convergence rates.
Design, analyze, and benchmark novel privacy-preserving learning algorithms (e.g., DP-SGD, private aggregation, and local/central differential privacy paradigms).
Collaborate with applied research and engineering teams to translate theoretical insights and mathematical proofs into practical, scalable machine learning solutions.
Explore intersections between statistical learning theory, optimization landscapes, and cryptographic primitives.
Author high-impact research papers for publication in top-tier machine learning and theoretical computer science conferences.
Stay at the forefront of foundational ML theory and privacy literature, identifying theoretical bottlenecks and proposing novel avenues of investigation.

The NPI Engineer is positioned at the interface between Engineering R&D and Manufacturing teams - providing technical and operational support throughout the product development and manufacturing lifecycle.
The role is responsible for ensuring product data accuracy, manufacturing readiness and resolving technical challenges encountered during assembly processes.
The position requires a strong technical foundation, attention to detail and a solid understanding of electronic components, PCB assemblies and manufacturing processes.

We are seeking a highly motivated NPI Engineer to support cross-functional Engineering R&D and Manufacturing teams.
The role requires hands-on experience with printed circuit board assemblies (PCBAs), from design through manufacturing and a solid understanding of product lifecycle management, component engineering, and manufacturing operations.
The NPI Engineer will bridge engineering design requirements with manufacturing execution, resolve technical challenges on the assembly floor and support successful product introductions in a dynamic, global environment.

Responsibilities
Support Product Lifecycle Management (PLM), including engineering changes, product data accuracy and configuration control.
Review and maintain Bills of Materials (BOMs), identifying discrepancies and risks.
Support component engineering, including part definition, catalogingd and alternative part evaluation.
Provide technical guidance on Surface Mount Technology (SMT), PCB assembly, and mechanical assembly processes.
Investigate manufacturing and quality issues, define corrective actions, and drive process improvements.
Collaborate with Engineering, R&D, Operations, and Manufacturing teams to ensure production readiness.
Develop and maintain manufacturing documentation, including assembly instructions and production specifications.

Our growing team is looking for a team player with versatile technical skills. You will engage in a cross-functional, collaborative environment that will take your debugging and technical skills to the limit while integrating cutting-edge technologies into our products.
In this role, youll be responsible for bringing groundbreaking wireless connectivity to the world through Wi-Fi, Bluetooth, and more. You will collaborate across departments to help craft wireless solutions that elevate the customer experience with our products and services.

In this role, you will be responsible for:
Work as part of a team to operate a large-scale test automation lab for our multiple products.
Test and integrate SW and HW deliveries from various global R&D teams, including managing, debugging, and failure analysis of automated tests.
Automate manual tasks for the lab and collaborate with technology teams to migrate more setups to the lab.
Constantly improve and innovate our lab procedures, HW setups, and SW tools.
This is a fixed-term position, with the possibility of extension.

We are seeking a Senior Systems Engineer for our System of Systems project, focused on developing innovative aerospace solutions. You will lead systems integration efforts and ensure seamless functionality across various systems.
Responsibilities:
Own the systems engineering of a complex System of Systems (SoS), maintaining the overall system-level view across multiple interconnected systems and subsystems.
Translate operational and customer needs into system architecture, clear and verifiable requirements, and system and interface specifications.
Define and manage interfaces and cross-system dependencies across radar, electro-optic, software and hardware teams.
Lead system integration, verification and validation activities, including system-level troubleshooting and resolution of technical issues, and participate in field integration and test campaigns (ground and live-fire test events).
Identify system risks, interface gaps and integration challenges early, and drive technical solutions with the relevant engineering teams.
Participate in and contribute to system design reviews (SRR, PDR, CDR) and technical trade-off studies from a System of Systems perspective.
Serve as the technical focal point for system-level and cross-system topics, working closely with multidisciplinary engineering teams and reporting key progress, risks and decisions to the Head of Systems Engineering.

Required Radar Algorithm Engineer.

This role is for a Design Verification Engineer who will enable us to produce fully functional first silicon IP designs. The responsibilities include all phases of pre-silicon verification including but not limited to: establishing DV methodology, test-plan development, verification environment development including stimulus and checkers, test-writing, debug, coverage, sign-off for RTL freeze and tape-out.

The position is relevant to all our sites: Herzliya, Haifa and Jerusalem.

In this role, you will be responsible for ensuring bug-free first silicon for part of the IP and are expected to: Develop detailed test and coverage plans based on the micro-architecture Develop verification methodology suitable for the IP, ensuring a scalable and portable environment. Develop verification environment, including all the respective components such as stimulus, checkers, assertions, trackers, coverage and more.

Every camera and sensing system we ship is used, every day, by hundreds of millions of people who simply expect it to work. Ensuring our systems are worthy of that expectation is this team's goal. We challenge products through the physical world to prove it, and to feed real-world evidence back into system design - measuring and analyzing the performance of multi-disciplinary optical sensing systems. This role is the analytical core of that work. You will define what we measure and why, mine large volumes of measurement data for the effect that actually matters, and take a question that has never been answered to a defensible answer. It is highly collaborative: you will work directly with module, optics, algorithm and system teams, and your conclusions will be the basis of their decisions. You will work alongside our lead system engineer as a peer, with problems allocated between you according to where the issue actually sits. We are looking for someone who genuinely enjoys digging into data until it gives up what it knows, and who wants to take that on with us.
Responsibilities
Own the characterization of system performance end to end - from risk and failure mode mapping through methodology definition, execution, analysis and reporting
Define metrics, testing & measurement methodology
Mine large data sets to separate isolate performance root causes
Correlate physical measurement to human perception - where the HW meets the user
Build the analysis capability the work requires - pipelines, tooling methods
Present and defend findings to module, optics, algorithm and system teams

In this visible role, you will be responsible for taking part of a SoC verification process of a large scale SoC.
You will develop verification test plans, tools, test benches, protocol monitors, and high-coverage stimulus vectors. Apply advanced techniques to achieve verification with the highest quality, productivity, and time-to-market. You will work closely with the design team to ensure timely delivery of quality designs.
Working with methods to accelerate verification time.

Imagine what you could do here. At our company, new ideas have a way of becoming great products, services, and customer experiences very quickly. Bring passion and dedication to your job and there's no telling what you could accomplish.
The people who work here have reinvented entire industries with all our Hardware products. The same passion for innovation that goes into our products also applies to our practices - strengthening our dedication to leave the world better than we found it. Join us to help deliver the next groundbreaking our products.

BIRD Aerosystems, a global provider of innovative defense solutions is seeking a skilled EO & Radar Systems Engineer to join our innovative engineering team. In this role, you will be at the forefront of designing, developing, integrating, and testing advanced electro-optical and radar systems for aerospace applications. You will work closely with multidisciplinary teams to develop cutting-edge solutions, optimize system performance, and support the transition of advanced technologies from development to production and field deployment. Responsibilities
* Design and develop advanced defense system based on electro -optical (EO) and radar technologies for aerospace platforms.
* Lead and support system-level integration, testing, and validation of EO and radar technologies.
* Define system requirements, architectures, interfaces, and technical specifications.
* Collaborate with multidisciplinary teams including hardware, software, algorithms, mechanical, production, and system engineering.
* Evaluate and integrate new EO, radar, sensing, and related technologies to enhance system capabilities.

Join the R&D team at BIRD Aerosystems as an EO System Engineer, where you will be responsible for developing and maintaining state-of-the-art electro-optical systems for aerospace applications.
Responsibilities: Design and develop electro-optical systems for aerospace applications. Collaborate with cross-functional teams to integrate systems into larger platforms. Conduct testing and validation of EO systems to ensure optimal performance. Troubleshoot and resolve technical issues related to EO systems. Document system specifications, designs, and testing procedures. Stay updated with the latest advancements in EO technology. Provide technical support and guidance to other team members.