Sort by
Refine Your Search
-
Listed
-
Category
-
Program
-
Employer
-
Field
-
, data analysis and fermentation optimization. Oversee project planning, execution, and resource allocation. Provide teaching, scientific guidance and mentorship to PhD and Msc students. Secure research
-
, generative design, building performance optimization, digital design methods (e.g., predictive modeling, multi-agent systems and algorithmic techniques for architectural design), digital design epistemologies
-
machine learning, computational modelling, and advanced data analytics can accelerate not only the discovery, characterization, and optimization of materials but also project assessment and communication
-
researchers passionate about making a difference in the field of science. About SCC SCC is a climate cluster organization established to create an optimal framework at SDU for groundbreaking, excellent and
-
optimization of novel organic reactions, as well as substrate scope investigation including isolation and characterization of products. You must have a two-year master's degree (120 ECTS points) or a similar
-
reagents, development and optimization of novel organic reactions, as well as substrate scope investigation including isolation and characterization of products. You must have a two-year master's degree (120
-
transformation, operational efficiency, and structural coherence Strong financial understanding, including cost control and gross margin optimization Excellent stakeholder management skills across academic
-
optimization of SERS substrates, Raman measurement, data analysis, and validation of results with reference methods such as high performance liquid chromatography (HPLC). You are expected to have a solid
-
translate fundamental insights in membrane technology into practical, impactful solutions. Responsibilities and qualifications Develop and optimize highly structured membranes for membrane distillation. Lead
-
on developing machine learning algorithms to support the use of complex urban simulators in decision-making under uncertainty. This PhD project shifts the focus from optimality to relevance in urban land-use and