Sort by
Refine Your Search
-
Listed
-
Category
-
Program
-
Field
-
implementation of these within optimized computer code, but also large-scale applications of the resulting methods to various chemical problems of interest. Candidates with a strong background in theoretical and
-
Optional: a separate page containing examples of python code you’ve written for bioinformatics projects or links to relevant repositories (e.g. GitHub) You may apply prior to obtaining your master's degree
-
) and geochemical speciation calculations (such as with PHREEQC or a similar code). We are running several projects in parallel, ranging from fundamental investigations of mineral-water-gas properties
-
pulses develop numerical codes to calculate the system dynamics by solving partial differential equations (e.g. Schrödinger equation, von Neumann equation) model the coupling to lattice vibrations (i.e
-
PhD scholarship in Runtime Multimodal Multiplayer Virtual Learning Environment (VLE) - DTU Construct
), serious gaming, agent-based simulation, knowledge of relevant research methodologies and practical experience with adequate state-of-the-art tools Very strong skills in coding (e.g., Python, C#, C++) and
-
Foundation Center for Biosustainability (DTU Biosustain) Recent progress in our ability to read and write genomic code, combined with advances in automation, analytics and data science, has fundamentally
-
. Experience in coding (e.g., Python) and in the use of Structural Analysis Software (e.g., OpenSees, Abaqus) is highly desirable. Ability to work independently and take initiative in planning and executing
-
potential market failures and prevention mechanisms. You will be combining theoretical analysis with practical applications, involving mathematical modeling, algorithm development, and coding. You should have
-
frameworks, applying existing frameworks, and implementing novel methodology in shared code repositories. You will also assist in instructing and guiding the research of MSc and PhD students. Qualifications As
-
code, combined with advances in automation, analytics and data science, has fundamentally changed the scope and ambition of harnessing the potential of biological systems. Big data approaches and