At a Glance
- Tasks: Design and optimise GPU/CPU performance for cutting-edge simulations in semiconductor technology.
- Company: Join Synopsys, a leader in innovative chip design and simulation.
- Benefits: Competitive salary, flexible work options, and opportunities for professional growth.
- Other info: Collaborative environment fostering creativity and technical excellence.
- Why this job: Make a real impact on next-gen tech that shapes our everyday lives.
- Qualifications: PhD or MS in Applied Mathematics with experience in engineering software development.
The predicted salary is between 60000 - 80000 £ per year.
We Are: At Synopsys, we drive the innovations that shape the way we live and connect. Our technology is central to the Era of Pervasive Intelligence, from self-driving cars to learning machines. We lead in chip design, verification, and IP integration, empowering the creation of high-performance silicon chips and software content. Join us to transform the future through continuous technological innovation.
You Are: An analytical engineer with a passion for scientific computing, applied mathematics, and advanced technology. With a strong academic background and hands-on experience in large-scale engineering software, you thrive in complex problem-solving environments and enjoy collaborating with diverse teams. Adaptable and creative, you are motivated by the impact of your work on consumer products worldwide. Expertise in numerical methods, high-performance computing, parallel programming, and machine learning enables you to tackle intricate challenges with dedication and curiosity. Strong communication skills, a proactive mindset, and a commitment to excellence round out your profile as an ideal contributor to our international R&D team.
What You’ll Be Doing:
- Designing and implementing GPU/CPU performance optimizations for large-scale TCAD simulations
- Developing distributed-computing solutions to enable efficient simulation of complex nanoscale devices
- Applying machine learning models to address emerging technology challenges in semiconductor simulation
- Performing numerical analysis of strongly coupled PDE systems to enhance simulation accuracy and speed
- Collaborating closely with Application Engineering and cross-functional teams to refine and validate solutions
- Contributing to the continuous improvement of the Sentaurus product line used by semiconductor companies, research institutions, and universities worldwide
- Engaging in code reviews, technical discussions, and knowledge sharing within a high-performing R&D culture
The Impact You Will Have:
- Drive innovations that enable next-generation chip design and simulation for global industry leaders
- Accelerate the development of consumer products—phones, cameras, cars, and more—by advancing simulation technology
- Enhance the performance and scalability of the Sentaurus product line, directly influencing semiconductor research and development
- Support the transition to smarter, more efficient devices by integrating advanced ML and HPC techniques
- Foster collaboration across teams and disciplines, promoting a culture of creativity and technical excellence
- Champion the adoption of new methodologies and tools, ensuring Synopsys remains at the forefront of innovation
- Mentor and inspire peers, contributing to the growth and diversity of the R&D engineering community
What You’ll Need:
- PhD or MS in Applied Mathematics or a closely related field, with 3+ years of experience developing large, complex engineering software
- Strong background in numerical methods, high-performance computing (HPC), and parallel programming (MPI, TBB, OpenMP)
- Proficiency in software design and programming, particularly in C++, CUDA, and Python
- Experience applying machine learning methods in an engineering or scientific-computing context
- Expertise in numerical analysis, especially with strongly coupled PDE systems
Preferred:
- Experience in applied physics, electrical engineering, or mechanical engineering
- Background in linear solver methods, discretization methods (FEM, FVM) OR physical modelling of semiconductor devices
Who You Are:
- Analytical and detail-oriented, with a strong problem-solving mindset
- Collaborative and open to diverse perspectives, thriving in a multicultural team environment
- Innovative and creative, always seeking new approaches and solutions
- Effective communicator, able to explain complex concepts to varied audiences
Staff Engineer (R&D Engineering) in Glasgow employer: Synopsys, Inc.
At Synopsys, we pride ourselves on being an exceptional employer that fosters a culture of innovation and collaboration. Our R&D team thrives in a dynamic environment where employees are encouraged to grow through continuous learning and mentorship, while contributing to groundbreaking technologies that shape the future. With a commitment to excellence and a focus on impactful projects, working at our location offers unique opportunities to engage with cutting-edge advancements in semiconductor simulation and machine learning.
StudySmarter Expert Advice🤫
We think this is how you could land Staff Engineer (R&D Engineering) in Glasgow
✨Network Like a Pro
Get out there and connect with people in the industry! Attend meetups, webinars, or conferences related to R&D engineering. You never know who might have a lead on your dream job or can introduce you to someone at Synopsys.
✨Show Off Your Skills
Create a portfolio showcasing your projects, especially those involving numerical methods or machine learning. This is your chance to demonstrate your hands-on experience and problem-solving skills, which are key for roles like Staff Engineer.
✨Ace the Interview
Prepare for technical interviews by brushing up on your knowledge of high-performance computing and parallel programming. Practice explaining complex concepts clearly, as strong communication skills are essential for collaborating with diverse teams.
✨Apply Through Our Website
Don’t forget to apply directly through the Synopsys website! It’s the best way to ensure your application gets seen by the right people. Plus, it shows your enthusiasm for joining our innovative team.
We think you need these skills to ace Staff Engineer (R&D Engineering) in Glasgow
Some tips for your application 🫡
Tailor Your CV:Make sure your CV reflects the skills and experiences that align with the Staff Engineer role. Highlight your expertise in numerical methods, high-performance computing, and any relevant projects you've worked on. We want to see how you can contribute to our innovative team!
Craft a Compelling Cover Letter:Your cover letter is your chance to shine! Use it to explain why you're passionate about scientific computing and how your background makes you a perfect fit for our R&D team. Don’t forget to mention specific technologies or methodologies you’ve worked with that relate to the job description.
Showcase Your Problem-Solving Skills:In your application, include examples of complex problems you've tackled in previous roles. We love seeing how you approach challenges, especially in areas like machine learning and simulation technology. This will help us understand your analytical mindset and creativity!
Apply Through Our Website:We encourage you to apply directly through our website for the best chance of getting noticed. It’s super easy, and you’ll be able to upload all your documents in one go. Plus, it shows us you’re serious about joining our team at Synopsys!
How to prepare for a job interview at Synopsys, Inc.
✨Know Your Stuff
Make sure you brush up on your knowledge of numerical methods, high-performance computing, and parallel programming. Be ready to discuss specific projects where you've applied these skills, especially in C++, CUDA, and Python. This will show that you’re not just familiar with the concepts but have real-world experience.
✨Showcase Your Problem-Solving Skills
Prepare to share examples of complex problems you've tackled in the past. Think about how you approached the problem, the methods you used, and the impact of your solutions. This is your chance to demonstrate your analytical mindset and creativity in action!
✨Collaborate Like a Pro
Since collaboration is key at Synopsys, be ready to discuss how you've worked with cross-functional teams in the past. Highlight any experiences where you’ve engaged in code reviews or technical discussions, as this shows you value teamwork and knowledge sharing.
✨Communicate Clearly
Practice explaining complex concepts in simple terms. You might be asked to describe your work to someone without a technical background, so being able to communicate effectively is crucial. This will showcase your strong communication skills and your ability to connect with diverse audiences.
