Project Description:

• The intern will engage with our team to enhance archaeological site detection using multispectral satellite imagery. No prior AI knowledge is required, but some Python coding ability is desirable. They'll begin by understanding the various satellite imagery types, focusing on multispectral analysis to identify potential archaeological features known as cropmarks.

  Key activities include selecting and analysing multispectral imagery from high-resolution commercial satellites, interpreting these images to identify variations indicative of archaeological remains, and contributing to refining detection algorithms. They'll work with Sentinel hub data to understand vegetation health changes over time, which helps reveal hidden archaeological sites, correlating this data with known sites to enhance detection accuracy.

  The intern will develop skills in handling and analysing large datasets and gain insights into the application of AI in archaeology. They will play a crucial role in advancing a more efficient system for archaeological risk assessment, contributing significantly to the field.

• Technically, the intern will develop proficiency in analysing and interpreting multispectral satellite imagery and managing large datasets, essential for detecting archaeological sites. Python coding skills will be enhanced, facilitating the manipulation and analysis of data. They'll gain experience in AI methodologies, particularly in training and refining algorithms for pattern recognition.

  Human skills include problem-solving, critical thinking, and project management. They'll improve communication skills by working with a multidisciplinary team and learn to present complex technical data effectively. The project will also enhance their research skills, learning to hypothesise, test, and iterate in a scientific manner.

• Find out more about SPIN and explore FAQs here.

Applicant Specification:

• The ideal candidate will have an undergraduate degree in geography, archaeology, or computer science. A basic understanding of satellite imagery or remote sensing and some proficiency in Python coding are highly desirable.

  Minimum requirements include strong analytical skills, attention to detail, and a keen interest in archaeology and technology. The applicant should be self- motivated, eager to learn, and possess good communication skills.

  Desirable requirements include experience with GIS software, a foundational understanding of AI and machine learning concepts, and previous exposure to project work in a related field. The ability to work independently and in a team, coupled with a proactive approach to problem-solving, will be advantageous. An enthusiasm for innovation and a willingness to embrace new challenges are also sought after traits.

Process details:

• 8 weeks minimum fixed term contract to be agreed with successful candidate

• In-person Induction Event to be held on Monday 24 June 2024, and an in-person/hybrid Showcase Event to be held in the Autumn of 2024

• 5 days holiday to be taken during the placement