
Tenure-Track Faculty in Machine Learning for Aerospace Engineering Sciences
Welcome to the University of Colorado Boulder, where we are seeking a highly motivated and talented individual to join our team as a Tenure-Track Faculty in Machine Learning for Aerospace Engineering Sciences. Our department prides itself on pushing the boundaries of aerospace engineering and we are looking for someone who shares our passion for innovation and discovery. In this role, you will have the opportunity to conduct cutting-edge research, teach and mentor students, and contribute to the vibrant academic community at CU Boulder. We are looking for candidates with a strong background in machine learning and a passion for applying this technology to the field of aerospace engineering. If you are driven, creative, and excited about the potential of machine learning in aerospace, we encourage you to apply for this position.
- Conduct cutting-edge research in the field of machine learning for aerospace engineering.
- Develop and teach courses related to machine learning and aerospace engineering.
- Mentor and advise graduate and undergraduate students in their research projects.
- Collaborate with other faculty members and researchers within the department and across the university.
- Actively participate in departmental and university-wide events and initiatives.
- Publish research findings in reputable journals and present at conferences.
- Pursue external funding opportunities to support research and projects.
- Stay updated on the latest developments and advancements in the field of machine learning and aerospace engineering.
- Engage in professional development opportunities to enhance teaching and research skills.
- Contribute to the academic community by serving on committees and attending departmental meetings.
- Foster a positive and inclusive learning environment for students from diverse backgrounds.
- Represent the university and department at external events and conferences.
- Collaborate with industry partners to apply machine learning techniques in solving real-world problems in aerospace engineering.
- Contribute to the overall growth and reputation of the department through active involvement in recruitment and retention efforts.
- Adhere to all university policies and procedures related to teaching, research, and professional conduct.
Phd In Aerospace Engineering, Computer Science, Or A Related Field With A Strong Emphasis In Machine Learning.
Demonstrated Research Experience In Applying Machine Learning Techniques To Aerospace Engineering Problems, Such As Designing And Optimizing Aircraft Structures Or Developing Autonomous Flight Systems.
A Strong Publication Record In Reputable Journals And Conferences, Showcasing Expertise In Machine Learning For Aerospace Applications.
Experience In Securing Research Grants And Funding, As Well As A Track Record Of Successful Collaborations With Industry Partners.
Prior Teaching Experience At The Undergraduate And/Or Graduate Level In Machine Learning Or Related Courses, As Well As A Commitment To Mentoring And Advising Students.
Programming
Data Analysis
Big Data
Machine Learning
Deep Learning
Algorithm design
Artificial Intelligence
Optimization
Statistical modeling
Image Processing
Pattern Recognition
Computational Modeling
Communication
Conflict Resolution
Leadership
Time management
creativity
Attention to detail
Teamwork
Adaptability
Problem-Solving
Empathy
According to JobzMall, the average salary range for a Tenure-Track Faculty in Machine Learning for Aerospace Engineering Sciences in Boulder, CO, USA is $80,000 - $120,000 per year. This can vary depending on factors such as experience, education, and the specific institution or company the faculty member is employed by.
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The University of Colorado Boulder, colloquially referred to as CU or Colorado, is a public research university in Boulder, Colorado. It is the flagship university of the University of Colorado system and was founded five months before Colorado was admitted to the Union in 1876.

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