We are seeking a dynamic intern with a flair for Machine Learning to join us to develop a machine-learning model for acoustic data. If you're a master's degree student, excited about AI and have some experience with Python, PyTorch, and Signal Processing, this opportunity is perfect for you!

This internship is for you, If you:

• Want to be part of an innovative team at the intersection of AI and manufacturing.
• Have the desire to work on real-world machine learning applications.
• Want to contribute to cutting-edge technology that makes a difference.
• You are studying and/or living in The Hague, Netherlands currently.

• Develop a machine learning model for our acoustic data.
• Use your skills in Python and PyTorch for data preprocessing and machine model training.
• Collaborate in a fast-paced team environment and contribute fresh ideas.

• Currently pursuing a Master's Degree in a related field (e.g., Computer Science, Engineering).
• Basic knowledge of Python and PyTorch.
• Interested in working with acoustic and audio data.
• Interest in AI, machine learning, and data quality.
• Interested in signal processing.
• Good problem-solving and communication skills.

Working at RESONIKS, you will:

• Immerse yourself in a pioneering company at a pivotal stage of growth.
• Address cutting-edge AI challenges in a vibrant and innovative environment.
• Receive a competitive internship compensation and a personal development budget.
• Embrace our culture of diversity, inclusivity, and open dialogue.
• Enjoy regular team events celebrating our shared success.

So, kick-start your career in the world of quality and sustainability in manufacturing. Apply now! Sending us your CV and a concise motivation letter to careers@resoniks.com. Let’s resonate with the future of quality and sustainability together.

"We are an equal opportunity employer, and all qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity or expression, pregnancy, age, national origin, disability status, genetic information, or any other characteristic.