Project Overview

The DiSTAP programme addresses deep problems in food production in Singapore and the world by developing a suite of impactful and novel analytical, genetic and biosynthetic technologies. DiSTAP is one of the five Interdisciplinary Research Groups (IRGs) of the Singapore-MIT Alliance for Research and Technology (SMART).  The research engineer will join an interdisciplinary team of chemists, engineers and plant biologists in the analysis and interpretation of Raman spectra data from plants, using advanced machine learning techniques. These analytical methods aim to uncover deep insights into plant health, growth patterns, and adaptations, potentially revolutionizing strategies for optimal crop production. Through this research, we aspire to pioneer innovative solutions for high-density and urban farming, laying groundwork for a more sustainable future.

Job Description

Successful candidate will be working closely with Prof. Giovanni Volpe and Dr. Gajendra Pratap Singh. The candidate's responsibilities will be:

– Analyze Raman spectra of plants to extract valuable information pertaining to plant health, growth, and nutritional content.

– Develop, implement, and optimize machine learning algorithms for predictive modeling and pattern recognition in spectroscopic data.

– Collaborate with a multidisciplinary team of chemists, engineers, and plant biologists to understand the implications and applications of the findings.

– Stay updated with the latest advancements in machine learning, spectroscopy, and plant science, integrating them as necessary to enhance the project outcomes.

– Publish research findings in peer-reviewed scientific journals and present at conferences or workshops.

Job Requirements

• PhD degree in Physics, Mathematics, Computer Sciences, Machine Learning, or related fields.
• Proficiency in programming languages, especially MATLAB and Python.
• Strict adherence to good laboratory practices, safety regulations, and protocols.
• Comfortable with using and troubleshooting custom-built software, including those without comprehensive user manuals.
• Collaborative mindset: ability to work cohesively in teams and interact productively with industrial partners.
• Excellent written and spoken English communication skills.
• Prior experience in Raman spectroscopy, imaging, and machine learning applications in spectroscopic data analysis is a plus.
• Demonstrated capability for hands-on experimental work and problem-solving is also a plus

If you want to find out more about the role, please contact Dr. Gajendra P Singh (gajendra@smart.mit.edu).

Interested applicants are invited to send in their full CV/resume, cover letter and list of three references (to include reference names and contact information). We regret that only shortlisted candidates will be notified.