python prediction application

We are currently developing a prediction application in Python, which analyzes and informs pesticides and pesticide residues on vegetables, which are still detectable after a certain time.
Now we are looking for a Python developer with enough experience to help us with this project.




Requirement: 

- Creative thinking and work
- Python experience 4+ years

Also, we are asking for the solution of the following 2 tasks:
( The goal is to tackle these on a conceptual level.
Perfect solutions/ production ready code is not required
Since the focus is on discussion and conceptualization, we recommend: jupyter notebooks )



1. 3d Ground Classification

2. Weld Defect Detection



1: 
We provide a 3 aerial LIDAR scan (input.las)
The goal is to classify ground points.
The aim is not 100% accuracy or Deep Learning based approaches, a “quick and dirty” solution suffices.
Recommended tools:
Point cloud processing
- Laspy
- Pdal
- Scikit

Visualization
- Potree
- Pptk
- Open3d
- CloudCompare

2. 
The goal is to use (unsupervised) image segmentation to locate possible defects in x-ray scans of weld.
Possible Tools:
OpenCV
CGAL
Sklearn.Cluster
The Use Case is to provide to aid to a human labelling or a weld scan review:
The defects are the black cracks and blobs in the grey weld
100% accuracy not required.§It suffices to provide hints “where to look” 



weld image: files attached
lidar: https://we.tl/t-w1sgSaLEUV