Hyperspectral imaging and analysis in outdoor environments with varying illumination conditions.

Student project:

Hyperspectral imaging and analysis in outdoor environments with varying illumination conditions.

Field Application Engineering - Leuven

What you will do

We are seeking an intern with hands-on skills and background in signal processing and possibly machine learning to join our team and conduct hyperspectral measurement campaigns together with hyperspectral image analysis. This role provides an excellent opportunity to apply your technical skills in real-world research setting and contribute to developments in hyperspectral imaging processing techniques. You will work closely with a multidisciplinary team to develop and test methods to optimize the spectral fidelity in varying outdoor illumination conditions.

We are seeking an intern with background in signal processing and basic machine learning to join our team and conduct measurement campaigns with hyperspectral cameras for outdoor environments. Different types of camera equipment, optic elements and light sources will be used. All our cameras are manipulated via user-friendly GUIs and/or python APIs. This role provides an excellent opportunity to apply your technical skills in real-world research setting and contribute to advancements in hyperspectral imaging and material discrimination. You will work closely with a multidisciplinary team to develop and test hyperspectral acquisition approaches in outdoor environments and with changing light conditions.

In short, the internship involves: 

• Field Application Engineering: participate in measurement campaigns taking indoor and outdoor measurements with different hyperspectral cameras. This involves prior equipment preparation and device and software testing.
• Data processing: under varying light conditions, different type of light references can be acquired. You will perform the required spectral calibration and pre-processing to compare the spectral fidelity of the different approaches.
• Hyperspectral analysis: you will compare the spectral fidelity and robustness of different measurement approaches. You may develop new methods of how to best do this assessment.
• Machine Learning Model Development: design, train, and evaluate simple machine learning models for material discrimination, with a focus on model robustness and accuracy. We have toolboxes and scripts available for this.
• Documentation and Reporting: keep clear documentation of measurements done, methodologies used for calibration/light normalization, code, and results. Regularly report findings to the project team and stakeholders. 
• Collaboration and Communication: work with senior researchers and developers to troubleshoot issues, incorporate feedback, and refine approaches based on experimental results. 

What we do for you 

• We have a diverse team of experts both from hyperspectral imaging and machine learning sides to supervise and support you. 
• We have a challenging problem where you have the freedom to help develop it in a specific direction. 
• You will join the Field Application Engineering team of Imec Leuven, which employs state-of-the-art imec hyperspectral and multispectral cameras and advanced hyperspectral data analysis. 
• You will be able to exchange views and knowledge with the Imec community of experts and scientists, widening your professional network. 
• At Imec Leuven we embrace diversity and thus give equal opportunities to intern candidates with diverse backgrounds.  
  
  

Who you are

• MSc student enrolled in Electrical Engineering, Physics, Computer Science, or a related field. 
• Signal Processing Skills: familiarity with preprocessing techniques like filtering or up sampling.  
• Hands-on Skills: you are motivated to learn the use of state-of-the-art hyperspectral cameras and lenses, but you are at the same time careful with handling of expensive and sensitive material.
• Basic Machine Learning Knowledge: Understanding of basic machine learning concepts, with hands-on experience in model building and evaluation (e.g., classification models, feature selection). 
• Programming Skills: Proficiency in Matlab. Knowledge of Python scripting is a plus. 
• Analytical Skills: Ability to analyse large datasets and extract meaningful insights to compare different approaches. 
• Language Skills: you communicate fluently for both oral and written English.
• Plus – Prior experience/knowledge of cameras and optics.
• Plus – More advanced machine learning or deep learning knowledge is a plus but not required. 

Interested

Does this position sound like an interesting next step in your career at imec? Don’t hesitate to submit your application by clicking on ‘APPLY NOW’.
Should you have more questions about the job, you can contact Carolina Blanch (blanch@imec.be).