PHD Graduate Student

Company Description

The Faculty of Science at Universiti Malaya is one of the oldest and most accomplished faculties within the university, established in 1959. It consists of two institutes and four departments: the Institute of Biological Sciences, Institute of Mathematical Science, Department of Chemistry, Department of Physics, Department of Geology, and Department of Science & Technology Studies. Serving as a major teaching and research center for Science & Technology in the region, the faculty is equipped with state-of-the-art research equipment and world-class facilities. The Faculty of Science in Universiti Malaya is recognized for its locally and internationally acclaimed researchers and diverse resources like Rimba Ilmu, zoological and geological museums, and research stations. It also manages the Malaysian Journal of Science.

Role Description

This is a full-time, on-site role for a PhD Graduate Student based in Kuala Lumpur. The PhD Graduate Student will be responsible for conducting research as part of their doctoral studies, engaging in data analysis, and writing scientific papers. Additionally, the graduate student will participate in laboratory work, collaborate with faculty members and other researchers, attend and present at conferences, and contribute to the educational missions of the faculty by assisting in the supervision of undergraduate students.

Qualifications

• A Master's or Bachelor's (First Class Honours) degree in Chemistry, Materials Science, or a related field.
• Strong Research and Data Analysis skills
• A foundation in synthetic chemistry is essential.
• Experience with Laboratory Work and Equipment
• A keen interest in or prior experience with computational chemistry or data science (experience with Python is a plus, but not a prerequisite).
• Proficiency in Scientific Writing and Publishing
• Excellent Communication and Collaboration skills
• Commitment to the field of Science & Technology
• University degrees related to any scientific discipline
• Prior research experience is advantageous
• Ability to work independently and in a team setting

PhD Studentship Opportunity: Machine Learning-Driven Ligand Design for Rare Earth Elements

Are you passionate about cutting-edge chemistry and computational science? Do you want to be at the forefront of solving critical challenges in sustainable technology? Join our dynamic team to pioneer the next generation of materials for the selective detection and extraction of
Rare Earth Elements (REEs)

.

The Project: Advancing Ligand Synthesis with Machine Learning

This project is situated at the vibrant intersection of
synthetic organic chemistry

,
coordination chemistry

, and
machine learning

. Rare Earth Elements are vital for modern technologies, from smartphones to electric vehicles, but their extraction and recycling pose significant environmental and economic challenges. Current methods often lack the required selectivity and efficiency.

Your research will focus on overcoming these limitations by:

• Designing Novel Ligands:
  Utilizing computational models and machine learning algorithms to predict and design organic ligands with high affinity and selectivity for specific REEs.
• Synthesizing and Characterizing:
  Bringing your computational designs to life through multi-step organic synthesis and characterizing the new compounds using state-of-the-art analytical techniques (NMR, MS, FTIR, UV-Vis, X-ray crystallography).
• Testing and Application:
  Evaluating the performance of synthesized ligands for the detection (e.g., colorimetric or fluorescent sensors) and extraction (e.g., solvent extraction, solid-phase extraction) of REEs from complex mixtures.
• Closing the Loop:
  Feeding experimental data back into the machine learning models to refine and improve predictive accuracy, creating a powerful design-synthesize-test-learn cycle.

This is a unique opportunity to develop a highly sought-after skill set in both experimental chemistry and data-driven materials design.

How to Apply

Ready to shape the future of materials chemistry?

Please send the following documents to [
]

with the subject line "
PhD Application: ML for REE Ligands

":

1. A detailed
   Curriculum Vitae (CV)
   , including a list of any publications.
2. A
   Cover Letter
   pages) outlining your research interests, relevant experience, and motivation for applying to this specific project.
3. Academic Transcripts
   from your undergraduate and postgraduate studies.
4. Contact information for
   two academic referees
   .

Application Deadline:

[
30 Oct 2025

]

We look forward to receiving your application.