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Machine Learning Cfd Jobs in Colorado (NOW HIRING)

... machine learning. * Understanding of fundamental aerodynamics as it relates to low Mach, steady and ... Perform 2D/3D blade and airfoil CFD using panel-methods and/or commercial CFD solvers * Performing ...

Machine Learning Cfd information

What are Machine Learning CFD jobs?

Machine Learning CFD (Computational Fluid Dynamics) jobs focus on integrating machine learning techniques with traditional fluid dynamics simulations and analyses. Professionals in this field use AI and data-driven models to accelerate simulations, improve prediction accuracy, and optimize fluid flow processes. These roles often require knowledge of both CFD principles and machine learning algorithms, and are commonly found in industries such as aerospace, automotive, and energy. Typical responsibilities include developing surrogate models for simulations, automating data analysis, and implementing deep learning approaches for complex flow problems.

How does a Machine Learning CFD professional typically collaborate with domain experts and software engineers in a project setting?

As a Machine Learning CFD (Computational Fluid Dynamics) professional, you’ll frequently collaborate with domain experts such as mechanical or aerospace engineers to ensure your models accurately reflect physical phenomena. You’ll also work closely with software engineers to integrate machine learning algorithms into simulation pipelines and optimize computational performance. Effective communication is key, as you’ll need to translate complex data-driven insights into actionable engineering solutions and vice versa. These collaborative efforts help streamline workflows, improve model accuracy, and ensure practical deployment of ML-enhanced CFD tools.

What is the difference between Machine Learning CFD vs Data Scientist?

AspectMachine Learning CFDData Scientist
Required CredentialsDegree in Engineering, Computer Science, or related fields; knowledge of CFD softwareDegree in Statistics, Computer Science, or related fields; strong programming skills
Work EnvironmentEngineering firms, aerospace, automotive industries, research labsBusiness, finance, tech companies, research institutions
Industry UsageSimulation, fluid dynamics, engineering analysisData analysis, predictive modeling, business insights

Machine Learning CFD focuses on applying machine learning techniques to computational fluid dynamics simulations, often within engineering contexts. Data Scientists analyze large datasets to extract insights and build predictive models across various industries. While both roles require programming skills and a strong analytical background, Machine Learning CFD emphasizes simulation and engineering applications, whereas Data Scientists focus on data-driven decision-making across diverse sectors.

What are the key skills and qualifications needed to thrive as a Machine Learning CFD (Computational Fluid Dynamics) Engineer, and why are they important?

To thrive as a Machine Learning CFD Engineer, you need a strong background in fluid dynamics, numerical methods, and machine learning, often supported by a degree in engineering, physics, or computer science. Familiarity with CFD software (such as ANSYS Fluent or OpenFOAM), programming languages like Python or C++, and machine learning frameworks (TensorFlow or PyTorch) is essential. Critical thinking, problem-solving, and effective communication are standout soft skills for interpreting data and collaborating on interdisciplinary teams. These competencies are crucial for developing innovative solutions that enhance simulation accuracy and computational efficiency in engineering projects.
What cities in Colorado are hiring for Machine Learning Cfd jobs? Cities in Colorado with the most Machine Learning Cfd job openings:

Conceptual Blade Design Engineer

Envision Energy

Boulder, CO

$115K - $150K/yr

Other

Posted 26 days ago


Job description

Job Openings >> Conceptual Blade Design Engineer
Conceptual Blade Design Engineer
Summary
Title: Conceptual Blade Design Engineer ID: 1053 Location: Boulder, CO Salary Range: $115,000.00 - $150,000.00
More about this job >
Description

Envision Energy's Global Blade Innovation Center (GBIC) was established in 2015 to develop an in-house blade design group. Blade design engineers from industry-leading OEMs, national labs, and top graduates have collaborated for the past 11 years, leveraging the best of their collective knowledge and experience to create a state-of-the-art design capability. Envision's in-house blade designs and technology have disrupted the Chinese blade market (100+ GW/year) and resulted in significant cost of energy reductions (LCOE) and an expanded Envision market share. Envision is currently seeking talented and highly motivated engineers to expand our team and further develop exciting new blade design capabilities and technologies.   

As a key member of the GBIC's conceptual design team, you will be responsible for the design and analysis of wind turbine blades. This includes the development of new blade technologies and associated computational tools and methodologies.  

The successful candidate will have most of the following qualifications:

  • MSc or PhD in engineering (Aerospace, Mechanical, Civil etc.), applied mathematics, or physics,
  • 5+ years of professional experience; ideally wind and/or aerospace or closely related industry. That said, recent MSc or PhD graduates with relevant research experience are still strongly encouraged to apply.
  • Understanding of multi-disciplinary design optimization (MDO) concepts and numerical optimization and associated techniques such as gradient-based search, genetic algorithms, and machine learning.
  • Understanding of fundamental aerodynamics as it relates to low Mach, steady and unsteady, turbulent and laminar, incompressible and external flow.
  • Understanding of applied aerodynamics as it relates to 2D airfoils, lifting wings, rotors, and horizontal axis wind turbines and associated analysis methods such as Blade-Element Momentum Theory, lifting-line and CFD
  • Proficiency in programming and mathematical modeling in MATLAB, Python, C/C++, or similar is critical. Experience with revision control software like Git or Mercurial is also an asset.
  • Understanding of structural mechanics and beam theory. Experience with composite structures is also an asset.
  • Understanding of aero-elasticity, basic turbine operation and control.
  • Understanding of numerical computational geometry such as NURBS
  • Familiar with AI tools to automate routine tasks and improve workflow efficiency.
  • Familiar with HPC systems and Linux
  • Demonstrated ability to make sound engineering decisions under conditions of uncertainty, incomplete information, and competing technical objectives, while balancing performance, manufacturability, cost, and risk. Proven ability to prioritize effectively and collaborate with multidisciplinary teams across diverse backgrounds.

It is not expected that the ideal candidate has all the qualifications above. What is compulsory however, is a strong desire to quickly learn and adapt combined with a sense of technical curiosity and a self-motivating/self-starting open mindset that will enable easy knowledge transfer.

Tasks and responsibilities of the conceptual design engineer may include:

  • Leading blade design trade studies by defining appropriate problem formulations, selecting suitable methodologies, critically interpreting results, and exercising engineering judgment to recommend design directions
  • Generating and interpreting design space explorations to identify meaningful trends, understand complex engineering trade-offs, and guide strategic design decisions under uncertainty.
  • Innovating and implementing novel design concepts and technologies that suit the current and future needs of the organization.
  • Contributing to and/or leading new software tool development efforts to support the design tasks mentioned above.
  • Contributing to and/or leading new blade design and technology campaigns.
  • Perform 2D/3D blade and airfoil CFD using panel-methods and/or commercial CFD solvers
  • Performing 2D airfoil design, analysis and optimization.
  • Managing, validating, and interpreting engineering datasets to ensure traceability, quality, and suitability for model development, design decisions, and technology maturation.
  • Planning and performing validation studies to continually improve the accuracy of computational models vs. field performance measurements.

The Conceptual Blade Design Engineer should have strong interpersonal, collaboration and communication skills and be able to clearly articulate the conclusions from complicated engineering analyses to both expert and non-expert groups alike. They are expected to use data-driven approaches along with their professional judgment and experience to solve open-ended and novel challenges. A minds-on / hands-on approach is expected within Envision's highly entrepreneurial corporate culture as you tackle new challenges. Desire and ability to work across different cultures and international time zones is also critical.

Candidates should expect up to 15% international travel.

Envision is an Equal Opportunity Employer. Employment decisions are made without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, veteran status or other characteristics protected by law.

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