Key Skills

Job Description

About BlueHeart Energy Founded in 2016, BlueHeart Energy set out to solve one of the biggest challenges in energy: creating heating and cooling systems that are efficient, affordable, and sustainable. After nearly a decade of research and development, we introduced the BlueHeart engine: a breakthrough thermoacoustic technology designed to deliver high performance with minimal energy use and zero carbon emissions across residential and industrial applications. Our work is driven by innovation, precision engineering, and a commitment to redefining heating and cooling for a sustainable world. The Internship Join our Engineering, Quality, and Testing teams and contribute to the development of a data-driven reliability validation framework for innovative heat pump technologies. As a Reliability Engineering Intern, you will work on developing statistical models that support reliability demonstration and validation planning for our products. You will help translate customer lifetime and reliability requirements into practical test strategies at system, and component level, including sample size determination, accelerated testing approaches, confidence level calculations, and reliability prediction methods. This internship is ideal for a master's student who enjoys combining engineering, statistics, data analysis, and product validation to solve complex real-world challenges. We are particularly interested in MSc students who are eager to apply analytical methods to reliability engineering and contribute to the development of future validation strategies within a fast-growing climate-tech company. What You’ll Do Translate reliability and lifetime requirements into system, and component-level requirements Develop statistical models for reliability demonstration testing Determine sample sizes based on reliability targets, confidence levels, and acceptable risk Define statistically sound validation plans for system, and component testing Investigate lifetime distribution models and reliability prediction methods Evaluate accelerated life testing methodologies and acceleration models Analyse data and assess relationship between results and reliability objectives Develop recommendations for future validation and qualification programs Work closely with the Testing, Engineering, and Quality teams What We’re Looking For Currently studying MSc Mechanical Engineering, Systems Engineering, Aerospace Engineering, Industrial Engineering, Data Science, or a similar field Strong interest in reliability engineering, statistics, and product validation Experience with data analysis tools such as Python, MATLAB, R, or similar Familiarity with statistical analysis and modelling techniques Analytical mindset with strong problem-solving skills Able to work independently and manage a research-oriented project Comfortable working with engineering data and technical requirements Good English skills (spoken and written) What We Offerb Internship allowance and travel allowance A friendly, international work environment Training and mentorship from experienced Test Engineers Hands-on experience with cutting-edge heat pump technology Access to mental health support via OpenUp Opportunity to develop practical engineering skills in a fast-growing climate-tech company Be part of a scale-up making a real impact on sustainability. Learn more about our mission here.

Core Responsibilities

Develop statistical models and validation plans to demonstrate product reliability, translating customer lifetime and reliability requirements into system- and component-level test strategies. Analyze test data, sample sizes, confidence levels, lifetime models, and accelerated testing methods, then recommend future validation and qualification programs in collaboration with Engineering, Testing, and Quality teams.

Requirements

Applicants should be pursuing an MSc in Mechanical, Systems, Aerospace, or Industrial Engineering, Data Science, or a similar field, with a strong interest in reliability engineering, statistics, and product validation. They should have experience with data analysis tools such as Python, MATLAB, or R, familiarity with statistical analysis and modeling, strong analytical and problem-solving skills, the ability to work independently, and good spoken and written English.

Benefits

• Internship Allowance
• Travel Allowance
• Training And Mentorship
• Mental Health Support