Sort by
Refine Your Search
-
of molecular data Experience with high performance computing Aptitude for team work, problem solving and collaborative relationships Excellent verbal and written skills in English Organizational dexterity and
-
requires the following skills: Familiar with the fabrication and characterization of porous functional materials as well as the purification of inorganic matrix. Able to perform catalytic and/or adsorption
-
deep learning techniques to improve image processing and trait prediction. Analyze large datasets generated by the Phenomobile.v2+ to identify key traits affecting crop performance under stress
-
. The successful candidate will conduct both field and laboratory trials to evaluate the performance of bioengineering solutions in enhancing soil physical and chemical properties, increasing carbon sequestration
-
on perovskite solar cell technology. The successful candidate will contribute to the development of high-performance perovskite-based solar cells through material synthesis, thin-film deposition, and large-scale
-
. Proven ability to perform multidisciplinary research and contribute to funded research programs. Proven ability to the planning, sourcing, and development of new initiatives and ongoing research activities
-
for developing and optimizing desalination processes, particularly reverse osmosis, with a focus on sustainability and efficiency. The work will involve improving the performance of treatment systems and proposing
-
methodologies for the synthesis and characterization of phosphorus-based products designed for various applications. This includes enhancing the performance of existing phosphate-based products such as
-
candidate will work on innovative solutions that integrate advanced technologies, urban data, and sustainable approaches to enhance the performance of waste management systems. Key Responsibilities
-
(e.g., Bioconductor, Galaxy, KEGG, Reactome, STRING). Proficiency in Python, R, and Unix/Linux-based environments for high-performance data analysis. Knowledge of biological network inference, causal