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Research Scientist, Mechanical Reliability

At Sentient Science, it’s not just that our toys are cool, which they are, it’s that our tech can benefit the environment and can change the world we work in. It’s that the work you’ll do here is unbelievably unique and incredibly rewarding. We make the unpredictable, predictable and we do it by bringing data, materials science, physics, and software together.

We build physics-based, DigitalClone models that predict and improve the lifespan of rotating machine parts from wind turbines to helicopters to rail tracks. Our models reduce costs through prognostics. If you’re flying a helicopter over the ocean, you are going to want to know well in-advance if the rotator is going to give out. That’s where we come in.

The opportunity

Based out of our Idaho Falls location, we have a newly created opportunity for a Research Scientist, Mechanical Reliability who is equally comfortable researching and developing models as they are interacting with clients and making presentations. Someone who can work independently or as part of the highly collaborative six-person Wind Turbine and Drive team.

This is a brand new role that will combine the exciting world of physics-based models with the application of statistical analysis and machine learning. It’s an opportunity to come in and define your role as you independently design, develop, and implement methods to represent the reliability of engineering systems based on our multi-scale modeling approach.

What you will work on

Life rollup. You will apply existing and new methodologies to increase the accuracy of our life predictability models. This includes conducting research, creating methodologies and connecting with universities to gain access to the most cutting edge processes and tools they are using.

Data presentation. You will interact with the customers and conduct research to identify how life predictions should be presented to the end user. You will determine what they want to see, how they want to see the data presented and manipulate algorithms to visually present the data that represents the life of the turbine or drive.

What’s in it for you

A rare opportunity. This is an opportunity to work like an academic but with more recognition, freedom and compensation. This is an exciting area of research with new, well funded projects every year. With our Headquarters based on the University of Buffalo campus, you will have access to their network, their library and research and their super computer.

Exposure. This is #PredictiveAnalytics gone live. It’s #EnergyTech and #Physics at its most exciting. Your career will grow as you gain exposure to every major wind turbine manufacturer in the world. But more importantly, this is fundamental research where you can apply your own findings to build the product that if successful, will be applied towards dramatically change the way manufacturers approach the build process and the inspection process. We are an elite company working on a global scale, the experience of witnessing your brainchild come to life is a huge level of professional satisfaction and personal pride.

Team membership. You will be part of a team of problem solvers. Academics who can apply their knowledge. Programmers who can innovate solutions to complex issues. People who will drop what they are doing to excitedly work on a challenge together.

Superpowers. Not really. But our head office in Buffalo does bear a striking resemblance to the X-Men Mansion.

So, how do we know that’s you? You have:

  • Background in Mechanical Engineering. You have ten years experience in a similar role. Alternatively, you have five years experience and a Masters or Ph.D. in mechanical engineering, industrial engineering, reliability engineering, statistics, or related discipline. You have expertise in statistical modeling methods, reliability best practice, engineering design and optimization.
  • Practical experience the following:
    • Reliability software e.g. Weibull++ or similar.
    • Prototyping using one of  Python, R, C/C++
    • Physics-based modeling, such as FEM, CFD, MD, MC, DFT, etc. This is a definite asset but not a requirement.
  • Knowledge. Your writing and presentation skills are outstanding. You thrive in an autonomous role yet you are highly collaborative and a strong team player.

Need any more reasons to join us?

Not very many companies can say their first project was a life and death situation. Sentient Science Corporation started out over ten years ago working on a model to predict when the rotating motors on American Armed Forces helicopters would give out. From there, we took our theories, our processes and our solutions and applied them to wind turbines and clean energy. Whatever our next stop is, we guarantee it will be just as momentous!

Recognized by the White House in 2014 with the Tibbetts Award and Bloomberg New Energy Finance Pioneers Award in 2016, we are far from sitting back and enjoying our success. Sentient Science engages more than a dozen Ph.D.s as part of our well-funded R&D team. To date, one of our greatest accomplishments is being the first company to map the material genome. Our competition is years behind us and we are moving at a pace that suggests they aren’t going to catch us any time soon.

Sentient Science is a company that credits our collaborative, innovative and frankly brilliant teams with our success. We are the kind of company where your work makes a difference and serves a purpose bigger than ourselves. Right now, the work we are doing is helping make the world a better place. It’s technology with a purpose. If you want to be part of that, you are passionate and you think you might have the skills to contribute to our progress, send us your qualifications here and we promise to consider them. To keep up with what’s going on at Sentient, follow us on LinkedIn.

All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, protected veteran status or status as an individual with a disability.

To apply, please click here.