Archaeological Remote Sensing Scientist - ML & LIDAR Lead

Delft University of Technology (TU Delft); Delft; On-site; EUR 55,000 - 75,000; Full time

Benefits offered by this job

Pension plan ABP

Flexible working week

Education funding

Leave hours flexibility

Health insurance discount

Job summary

TU Delft (Delft University of Technology) seeks a computational scientist to lead ML-based analysis of remote sensing data for archaeology within the MAPHSA project. You will develop methods to extract hidden information from large datasets, coordinate collaboration with partners, and publish results.

You will supervise staff and students, contribute to funding and educational activities, and work with the Department to advance remote sensing and AI applications in archaeology.

Qualifications

• PhD in Archaeology with knowledge of pre-Columbian archaeology.
• Working knowledge of state-of-the-art Machine Learning methods.
• Experience with remote sensing methods including LIDAR and spectral sensing.
• Ability to efficiently process large data sets.
• Fluent in Spanish and English, spoken and written.
• Proven ability to acquire research funding.
• Experience in education, supervising BSc/MSc/PhD theses and coordinating projects.

Responsibilities

• Lead development of methodology to identify and interpret sparse information in remote sensing data.
• Coordinate the MAPHSA project and communicate results to partners and through publications.
• Supervise staff and students and contribute to departmental funding and education activities.

Skills

Machine Learning

Remote sensing

LIDAR

Data processing

Communication

Education

PhD in Archaeology

Tools

Python

MATLAB

GIS software

Job description

TU Delft (Delft University of Technology) seeks a computational scientist to lead ML-based analysis of remote sensing data for archaeology within the MAPHSA project. You will develop methods to extract hidden information from large datasets, coordinate collaboration with partners, and publish results.

You will supervise staff and students, contribute to funding and educational activities, and work with the Department to advance remote sensing and AI applications in archaeology.