Firmware Validation Student jobs in Israel

We are looking for a talented student to help us with our research and software development projects. In this role, you will work closely with multiple research and engineering teams to make cutting-edge NLP/MM models more efficient, optimize software, and contribute to internal frameworks and open-source projects.

As a Research student, you will focus on:-

• Examining novel methods, analyzing performance, and developing efficient algorithms to improve the efficiency of NLP/MM models.
• Participating in research projects with top researchers and engineers at Intel and in academia
• Actively contributing to the open source community.

• BSc, MSc, or PhD in Computer Science, Computer Engineering, or a related field with at least one year until graduation and availability to work three days per week.
• Strong software engineering capabilities in Python, Java, Go, Rust or C/C++.
• Experienced working with PyTorch or Tensorflow.
• Theoretical background in Deep Learning and/NLP/MM.
• Excellent written and verbal communication skills for expressing technical ideas and initiatives.

Extra points are given for:

• Previous hands-on experience with NLP/MM methods and models.
• Experience in mapping and understanding the performance of neural network models, model optimization on CPU/GPU hardware.
• Past publications in top machine-learning or NLP/MM venues.
• Experience with popular open source deep learning and AI libraries, such as Hugging face's Transformers, TGI, vLLM, and DeepSpeed
• Experience with full-stack development, building UIs and visualizations.

• Currently pursuing a Bachelor’s, Master’s, or PhD degree in Computer Science, Linguistics, Statistics, Biostatistics, Applied Mathematics, Operations Research, Economics, or Natural Sciences, or equivalent practical experience.
• Experience in one area of computer science (e.g., Natural Language Understanding, Human Computer Interactions, Generative Media, Computer Vision, Machine Learning, Deep Learning, Algorithmic Foundations of Optimization, Quantum Information Science, Data Science, Software Engineering, or similar areas).
  

• Currently enrolled in a full-time degree program in EMEA and returning to the program after completion of the internship.
  
• Experience as a researcher, including internships, full-time, or at a lab.
  
• Experience contributing to research communities or efforts, including publishing papers in major conferences or journals.
  
• Experience with one or more general purpose programming languages (e.g., C/C++, Java, MATLAB, Go, Python, etc.).
  

• Create visual content – presentations, videos, and photos – for internal and external communications.
• Support internal initiatives with creative ideas and engaging materials.
• Collaborate with teams to deliver impactful visual messaging.
• Manage creative projects from concept to execution.
• Stay up-to-date with trends and tools in visual communication.
•– helping plan and produce internal events, ceremonies, and engagement initiatives that foster a positive and inclusive workplace culture.

Requirements

• First/second-year student in Communication, Marketing, Design, Film, or related field.

• Creative thinker with strong visual storytelling skills.
• Experience in presentation design, video editing, and photography.
• Proficiency in tools like PowerPoint, Canva, Adobe Premiere, CapCut.
• Strong interpersonal and communication skills.
• Fluent in Hebrew and English.
• Social media experience – advantage.
• Passionate, proactive, and hands-on.

Yield engineers play a critical role in analyzing production data, identifying process deviations, and driving improvements to maximize product quality and output. As a Yield student, you will work alongside experienced engineers, support real-time manufacturing needs, and contribute to the continuous improvement of yield performance.
Responsibilities:
• Collect, analyze, and interpret inline and yield data from manufacturing processes.
• Identify trends, anomalies, and root causes for inline deviations and yield loss using statistical tools and engineering methods.
• Collaborate with process, equipment, and integration engineers to propose and implement corrective actions.
• Support the development and validation of models for process control and optimization.
• Document and communicate results clearly to cross-functional teams.
Why Join Us?
• Be part of a high-impact team driving quality and efficiency in semiconductor manufacturing.
• Gain hands-on experience with advanced technologies and data-driven engineering.
• Work in a dynamic, supportive environment with opportunities for growth and learning.

• M.Sc. student in Materials Engineering, Chemical Engineering, Mechanical Engineering, or Data Science.
• Strong analytical skills and experience in data analysis and problem-solving.
• High level of initiative and ability to self-learn.
• Experience with data analysis tools such as Python, JMP, Excel, or similar-advantage.
• Solid understanding of manufacturing operations and statistical process control-advantage.
• Ability to multitask and work under tight deadlines.
• Ability to work at least 20 hours per week (2.5 days a week).
• At least 2 years until graduation-required.

Engineering groups lead continuous improvement of processes and tools stability, reduce variance, cost reductions projects, and meet targets in an optimal way.

What will you do?

• You will work closely with expert engineers to support day-to-day engineering advanced work: support production needs, responsibility for highly advanced processes, and equipment stability.
• Be responsible for the implementation of new processes and methods, Proactive detection of malfunctions, Troubleshooting, Etc. using cutting-edge tools and methods.
• Take a part in implementing groundbreaking Automation solutions in Engineering and quality management systems to ensure fast response to production line needs.
• In this role, you'll be getting the experience you need, with the right balance of work and studies.

What are we looking for?

• B.Sc. Student of Mechanical Engineering, Materials Engineering, or Chemical Engineering
• Ability to work at least 20 hours per week. (2.5 days a week)
• 2 years until graduation- required
• Strong data analysis abilities and data systems orientation.
• Ability to work independently and be a team player
• Excellent English
• High knowledge of statistical data analysis- advantage