5 Environmental Science jobs in Singapore

The School of Materials Science and Engineering is looking for a highly motivated candidate to join us as a Project Officer (PO). The PO will join an MOE funded project led by Prof Ng Kee Woei. The project aims to upcycle keratinous waste for the bioplastics development. The PO will be responsible to develop and optimize the formulation of keratin-based bioplastics, characterize the produced bioplastics and assess its biodegradation profile in soil.
Key Responsibilities:
Conduct thorough literature review and generate periodic updates
Extract the keratin protein
Formulate and optimize keratin-based bioplastics
Characterize the keratin-based bioplastics properties (e.g. Mechanical strength, FTIR, SEM, degradability, permeability, water contact, etc.)
Analyse and interpret research data
Develop and optimize protocols
Manage logistical issues and laboratory inventory.
Participate in collaborative work within multidisciplinary team and external collaborators
Assist the generation of periodic progress report as required by funding agency
Job Requirements:
Bachelor’s degree in Materials Science/Chemistry/Environmental Engineering/Biology or related fields
Experience in polymers, biomaterials research and material characterization required (e.g. Mechanical strength, FTIR, SEM, degradability, permeability, water contact, etc)
Experience in environmental science and engineering will be a bonus
Good communication and writing skills
Good coordination/project management skills
Able to plan and execute experiments with minimal supervision
Able to take initiative to improve processes and troubleshoot problems
Able to organize well and adhere to deadlines
We regret that only shortlisted candidates will be notified.
Hiring Institution: NTU
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Overview
Research Fellow (Chemical Engineering/Material Science/Chemistry/Environmental Engineering) at Nanyang Technological University Singapore. The School of Chemistry, Chemical Engineering and Biotechnology is seeking a full-time Research Fellow.
Responsibilities
Development of new machine learning modeling approaches
Development of new advanced control and optimization algorithms
Optimization of carbon capture process operation
Provide regular project updates to principal investigator and funding agency
Report writing/presentation
Qualifications
PhD degree in an engineering field related to this project
Experience in dynamic modeling, machine learning and optimization & controls
Having basic knowledge in carbon capture, utilisation and storage (preferable)
Good command of English, both oral and written with ability to communicate effectively with a wide range of individuals and professional groups
Hiring Institution: NTU
We regret that only shortlisted candidates will be notified.
Seniority level
Entry level
Employment type
Full-time
Job function
Engineering and Information Technology
Industries
Higher Education
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Research Position Overview

We are seeking a highly skilled researcher to contribute to our cutting-edge research programme in the Human Potential Translational Research field.

The successful candidate will collaborate with our team on multidisciplinary projects focusing on heat, environment, and human health. Key tasks include analysing environmental exposures and health outcomes using advanced statistical and machine learning methods, developing risk models and decision-support tools for climate resilience, and communicating research findings through high-quality publications and reports.

The ideal candidate will have a PhD in environmental/climate science, data science, epidemiology, public health, or a closely related field, proven expertise in statistical modelling and machine learning for large and complex datasets, proficiency in Python and/or R for time-series and sensor data analysis, interest in or experience in environmental exposure assessment or related health research, a strong track record of peer-reviewed publications, excellent written and verbal communication skills, and the ability to work independently and in a multidisciplinary team.

Requirements:

• Education: PhD in environmental/climate science, data science, epidemiology, public health, or a closely related field.
• Skills: Statistical modelling and machine learning for large and complex datasets, Python and/or R programming languages for time-series and sensor data analysis.
• Experience: Environmental exposure assessment or related health research, peer-reviewed publications.
• Personal Qualities: Excellent written and verbal communication skills, ability to work independently and in a multidisciplinary team.

Benefits: Remuneration will be commensurate with qualifications and experience.

As a Research Assistant in our project, your work will directly contribute to developing new methods for long-term monitoring and understanding how environmental factors influence mobility and health.

• Machine Learning Pipeline Development:
• Assist in evaluating and analyzing functional assessment data.
• Help develop new machine learning pipelines to extract features from wearable IMU sensors, GPS, eye-tracking glasses image data, and other sensors for both short and long-term monitoring.
• Adapt processing pipelines for long-term monitoring data collected in naturalistic, real-world settings.
• Collaborate on data preparation for visualizations of collected data to explore, validate, and interpret the outputs of data processing pipelines.
• Conduct literature reviews and perform analysis on built environment and gait features.
• Documentation & Reporting:
• Maintain organized records of data collection protocols, processing steps, and algorithm versions.
• Prepare regular progress reports on data collection, processing, and pipeline development, supported by clear visualizations.
• Contribute to the preparation of technical documentation, manuscripts, and presentations.
• Assist and participate in field data collection.

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Required Skills and Qualifications
• Bachelor's Degree or equivalent in Data Science, Computer Science, Biomedical Engineering, or a related field.
• Proficiency in Python and MATLAB.
• Strong foundation in signal processing and machine learning.
• Excellent problem-solving skills and ability to work effectively in a collaborative research setting.
• Good communication and interpersonal skills.

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Benefits
• Diverse workplace with opportunities for mutual learning.
• Inclusive working environment.
• 25 days of annual leave for fixed-term contracts.
• 1 day of Birthday Leave.
• Annual dental benefits.
• Comprehensive healthcare insurance coverage.
• Flexible hybrid work arrangement.
• Abundant networking opportunities across various disciplines.

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Curious? So Are We!

We look forward to receiving your online application with the following documents:

• Cover letter explaining your interest in the project and position.
• Comprehensive CV, specifically tailored to this position including previous projects in MATLAB and/or Python.
• Academic certificates and transcript of records.