At a Glance
- Tasks: Develop and implement models for biological systems using cutting-edge computational techniques.
- Company: Join Coherence Neuro, a pioneering company in implantable technologies.
- Benefits: Enjoy competitive salary, share options, daily meals, and flexible working hours.
- Other info: Collaborative team culture with excellent professional development opportunities.
- Why this job: Make a real impact on life-changing technologies in a dynamic environment.
- Qualifications: Advanced degree in relevant fields and strong expertise in finite element methods required.
The predicted salary is between 50000 - 70000 € per year.
Coherence Neuro is a fast-growing, venture-backed company pioneering implantable technologies that interface with the human body to address critical unmet medical needs. We are looking for driven individuals passionate about pushing the boundaries of engineering and science to solve complex biological challenges. In this early-stage environment, we seek versatile team members with a hands-on approach and a willingness to learn quickly and adapt. We value diversity and encourage applicants from all backgrounds to join us in our mission.
We are seeking an enthusiastic and driven Computational Biophysicist who is passionate about using computational modelling to inform key product design decisions and enable patient-optimized therapeutics. The successful candidate will be based within the data science and computational modelling team and will also work closely with the product development and translation teams.
Key Responsibilities- Develop and implement finite element models of biological systems with a focus on electromagnetic (EM) and thermal dynamics in tissue.
- Design and simulate coupled multiphysics problems (e.g., EM–thermal interactions, bioelectric phenomena).
- Build subject-specific models by integrating MRI/CT imaging data into high-quality computational meshes.
- Perform segmentation, geometry processing, and mesh generation from medical imaging datasets.
- Validate models against experimental or clinical data, particularly for EM field distribution and heat transfer in biological media.
- Conduct sensitivity analyses and parameter optimization for EM and thermal simulations.
- Collaborate with cross-functional teams to translate imaging and modeling outputs into actionable insights.
- Clearly document and organize findings for key stakeholders.
- Advanced degree (MS/PhD) in Biophysics, Biomedical Engineering, Electrical Engineering, Mechanical Engineering, or related field.
- Strong expertise in finite element methods (FEM) with emphasis on electromagnetics and heat transfer.
- Hands-on experience with FEM tools supporting multiphysics (e.g., COMSOL, ANSYS, Abaqus).
- Experience modeling EM fields in biological tissues and associated thermal effects (e.g., RF heating, bioelectric interactions).
- Proficiency in medical image processing and segmentation, particularly MRI-based workflows.
- Experience generating meshes from imaging data and working with complex anatomical geometries.
- Strong programming skills in Python for simulation workflows and data processing.
- Solid understanding of tissue properties, bioelectricity, and thermal transport in biological systems.
- Strong analytical and problem-solving skills with ability to work across disciplines.
- Proficient oral, communication, and organizational skills and can work collaboratively within a close team setting.
This role is an integral part of the Computational Modelling and Product Development teams and reports directly to the Data & Computational Lead.
Benefits- Competitive salary and share options.
- Daily meals and snacks provided.
- Professional development support and training opportunities.
- Flexible working hours and travel opportunities (sites in Australia, UK, and US).
- A chance to work on impactful, life-changing technologies in a dynamic, innovative environment.
- Healthcare, dental, and vision.
- 401k with company matching.
- Industry-leading paid time off (PTO) – 20 days/year + holidays.
- Company-matched pension.
- Industry-leading paid time off (PTO) – 25 days/year + England bank holidays.
Computational Biophysics Engineer employer: Coherence
Coherence Neuro is an exceptional employer for those passionate about engineering and science, offering a dynamic and innovative work environment where employees can contribute to groundbreaking implantable technologies. With a strong emphasis on professional development, flexible working hours, and a commitment to diversity, team members are encouraged to grow and adapt while working collaboratively on impactful projects that address critical medical needs. Located in a fast-paced, early-stage setting, employees enjoy competitive benefits, including generous paid time off and opportunities for travel, making it a rewarding place to advance one's career.
StudySmarter Expert Advice🤫
We think this is how you could land Computational Biophysics Engineer
✨Tip Number 1
Network like a pro! Reach out to professionals in the field of computational biophysics on LinkedIn or at industry events. A friendly chat can open doors that a CV just can't.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your projects, especially those involving finite element methods and medical imaging. This will give potential employers a taste of what you can bring to the table.
✨Tip Number 3
Prepare for interviews by brushing up on your technical knowledge and problem-solving skills. Be ready to discuss your experience with FEM tools and how you've tackled complex biological challenges in the past.
✨Tip Number 4
Don't forget to apply through our website! It’s the best way to ensure your application gets seen by the right people. Plus, we love seeing passionate candidates who are eager to join our mission!
We think you need these skills to ace Computational Biophysics Engineer
Some tips for your application 🫡
Tailor Your CV:Make sure your CV reflects the skills and experiences that match the job description. Highlight your expertise in finite element methods and any hands-on experience with relevant tools like COMSOL or ANSYS. We want to see how you can contribute to our mission!
Craft a Compelling Cover Letter:Your cover letter is your chance to shine! Share your passion for computational biophysics and how it aligns with our goals at Coherence Neuro. Let us know why you're excited about the role and how you can help push the boundaries of engineering and science.
Showcase Your Projects:If you've worked on relevant projects, whether academic or professional, make sure to include them! Describe your role, the challenges you faced, and the outcomes. This gives us insight into your problem-solving skills and hands-on approach.
Apply Through Our Website:We encourage you to apply directly through our website. It’s the best way to ensure your application gets to us quickly and efficiently. Plus, it shows your enthusiasm for joining our team at Coherence Neuro!
How to prepare for a job interview at Coherence
✨Know Your Stuff
Make sure you brush up on your knowledge of finite element methods and their applications in biophysics. Be ready to discuss specific projects or experiences where you've used tools like COMSOL or ANSYS, as well as any challenges you faced and how you overcame them.
✨Show Your Passion
Coherence Neuro is all about pushing boundaries in engineering and science. During the interview, express your enthusiasm for computational modelling and how it can impact patient care. Share any personal projects or research that highlight your passion for the field.
✨Collaboration is Key
Since this role involves working closely with cross-functional teams, be prepared to discuss your experience collaborating with others. Think of examples where you successfully communicated complex ideas or worked together to solve a problem, especially in a team setting.
✨Ask Insightful Questions
Prepare thoughtful questions about the company's projects, culture, and future directions. This shows you're genuinely interested in the role and helps you assess if it's the right fit for you. Consider asking about their approach to integrating imaging data into models or how they validate their simulations.