Battery Modeling Engineer
We are looking for our next team member, a battery modeling engineer, to help us further develop our product and ourselves.
Are you interested? Click on the button, send us your CV, and come by our office at Kungsgatan 11 in central Gothenburg, Sweden.
We are Nortical!
Nortical improves battery efficiency. We do this by analyzing live battery data in order to compile battery insights that we use to give advice on how to utilize them better in the future.
We are smack in the middle of the creation of a completely new value chain. As the world is electrifying, batteries are becoming the centerpiece of both existing and new business models and products. You will work in the very center of this change together with a diverse team of like-minded individuals, people truly taking an active role in shaping the future of electrification and how batteries will be used.
We are now looking for someone with a passion for battery modeling and specifically, non-linear estimations.
This is in order to efficiently estimate battery (model) states and parameters, as they play a key role in the design of reliable battery aging and other behavior models.
What You´ll Do
As a start-up team, we all have diverse tasks, but your main focus will be:
Design on and off-board estimators for battery model parameters.
Continue developing our architecture for collection and analysis of battery usage data.
Propose new functions that deliver value to our vast range of battery users.
Propose a functional architecture that uses on-board SoH estimates, battery usage patterns, operating conditions, and predictive aging models for extended RUL predictions.
Develop estimation algorithms for predictive aging modeling within a control system framework. In this regard, the use of machine learning and statistical modeling methods may also be promising for early detection of aging patterns and prediction of RUL using individual vehicle or fleet-level battery diagnostic data.
Analyze and verify the performance of the proposed scheme thoroughly using lifetime aging data for lithium-ion batteries under different load cycles and operating conditions.
We place great value in intelligence, team sense, and self-drive. But skills are important too. Here follows the skill set that we believe is key for accomplishing your tasks.
Excellent knowledge in nonlinear filtering, nonlinear estimation and linear control systems.
Background in battery system estimation and controls or similar knowledge.
High level of fluency in the Python programming language.
Experience in writing efficient code to process and analyze large data sets.
Confident working in a start-up environment where we sometimes have to find our own way in unchartered territory.
Self-motivated and meticulous in your problem-solving approach. You should love to learn new things and conduct experiments.
Proficiency in English (Swedish not required).
Knowledge of Rust, .js and Elixir languages
Familiarity with electro-thermal and aging dynamics of lithium-ion batteries and some previous experience with machine learning methods for health prognostic applications
Diversity makes a difference
You are welcome to Nortical as the person that you are, no matter where you come from, what you look like, or what your favorite battery chemistry is. The more minds and voices we have, the stronger our business will be, the more we will thrive and develop. It´s in our diversity that we find the secret sauce for our revolutionizing products and creating a better tomorrow.
Does this sound interesting? Please get in touch with Us as soon as possible. We apply a continuous selection process and interviews will be held continuously. So click that apply button or mail us at email@example.com and share your CV.