Research Assistant (AI/Remote Sensing Software Engineer) - Syed Babar Ali School of Science and Engineering (SBASSE)
Monday, January 31, 2022

Job Description

Job Description: 

Position Purpose: 

The selected candidates will work with one of their respective teams analyzing and solving problems using deep learning and machine learning techniques along with remote sensing & GIS. The problems will be related to crop monitoring, forest mapping, water quality monitoring and other aspects of hydrological sensing. Their contribution as a team member will be design and development of an integrated software system common across all solutions along with the customization with respect to their particular problem.

Main Responsibilities

  • Applicants must possess a solid foundation in computer science along with good understanding of machine learning, remote sensing and GIS.
  • Work closely with other ML Engineers, Software Engineers and Researchers on a daily basis.
  • Familiar with the basics of computer vision and machine learning. Experience would be preferred.
  • Familiar with the annotation of data for deep learning dataset generation.
  • Analyzing geological data and fulfilling remote sensing related queries with the help of GIS lead.
  • Familiar with GIS and remote sensing related open source software.

Work Environment:

  • Research lab
Skills: 
  • Understanding of Deep Learning theory.
  • Basic knowledge map development and integration.
  • Preferable candidate must have some prior experience in remote sensing and GIS related project.
  • Understanding and hands-on experience in: Image segmentation algorithms;
  • Machine learning and deep learning.
  • Familiarity with machine learning packages such as TensorFlow or PyTorch
Qualification: 
A BS or MS degree in computer science, engineering or related field (must have completed it) from a HEC recognized institution.
Knowledge: 
  • AI/Remote Sensing Software Engineer
Experience: 
At least 6 Months

LUMS is an equal opportunity employer. We celebrate diversity and are committed to building an inclusive workplace for all our employees. We do not discriminate on the basis of gender, race, religion, caste, ethnicity, age, non-disqualifying physical or psychological disability or social status. Candidates belonging to minority groups are encouraged to apply.