Danni's Ph.D. focuses on improving the flotation of fine valuable lithium minerals through the formation of small hydrophobic flocs. She received her Bachelor’s degree in Science and her Master’s degree in Chemistry both from the University of Melbourne. She has spent a year at the Chinese Academy of Science. Before joining the FBICRC, she worked in the ARC Centre of Excellence in Exciton Science. There, she studied nanoparticle synthesis and the use of SERS substrates for point-of-care analyte sensing.

Jiancheng Lin conducted undergraduate research at UNSW Sydney, Australia where he received his Bachelor of Engineering (Honors) in Chemical Engineering in 2021. He then continued to pursue his Ph.D. degree in chemical engineering at UNSW Sydney under the supervision of Prof. Guangzhao Mao. His research focuses on the understanding of electrocrystallization of charge-transfer complexes and their applications for gas sensing. Jiancheng would like to continue broaden his research experience and apply his skill in industrial related research and development.

Ariel is a postgraduate researcher specialising in the domain of optical communication research. She was conferred with a Master of Science degree in electrical engineering and computer science in the University of Southern California, USA, in 2021. Her research gravitated towards the machine learning and computer algorithms. She was awarded an Honors distinction during her master degree. In 2023, she initiated her doctoral research at the University of Melbourne.

Meet Kesewa, a passionate PhD student whose research centers around perishable agri-food supply chains and decision-making models. With a broad range of skills, including data analysis, mathematical modeling, and programming, Kesewa is committed to minimizing food waste and enhancing distribution efficiency. Kesewa is thrilled about the prospect of an internship that connects academic research with practical industry applications, as it aligns perfectly with her ultimate objective of making a positive impact on the global food supply chain.

Christina's passion lies in artificial intelligence, especially Large Language Models and machine learning. Proficient in machine learning, natural language processing, and Python/Matlab, she aims to apply her skills in real-world, commercial applications, merging her academic expertise with practical problem-solving. She is also open to new filed of research.

Laurene is a second-year Ph.D. student at USyd, focusing on the Australian Tick Microbiome Project. She initiated this project in collaboration with UNSW to characterise microorganisms in Australian ticks. Through this research, she hopes to provide clarity and remove the controversy surrounding tick-borne diseases in Australia, allowing patients to better access diagnostics and treatments. She is also an experienced Technical Assistant (USyd and Amgen), Science Communicator (UNSW Science Ambassador) and Teacher (highschool and undergraduate classes at UNSW and USyd).

With a diverse academic background spanning Aerospace Engineering, Bioinformatics, Public Health, and Information Technology, Aziida seeks a challenging position in Engineering. She aspires to leverage her expertise in Machine Learning, advanced modeling, data analytics, and Natural Language Processing to contribute to cutting-edge research, innovation, and lifelong learning. Proficient in SPSS, MATLAB, Python, R, and Microsoft Office Suite, Aziida is committed to making a significant impact in the field, making her an ideal candidate for internships.

Balaji Dasari is a proficient researcher with a strong academic background. His expertise spans econometrics, financial analysis, and artificial intelligence, with a particular focus on modeling and understanding the influence of news on commodity markets. His commitment to advancing research in these fields drives his interest in pursuing an internship, where he can apply and further develop these academic skills.

Martin is a Mechanical Engineer by background. His research interest include pipelines,material science,corrosion,artificial intelligence and machine learning.