35 parallel-processing-bioinformatics PhD positions at Utrecht University in Netherlands
Sort by
Refine Your Search
-
background in hydrology, earth system science, atmospheric science, agroecology or other appropriate fields. You will work on the project “Physics-informed AI-modelling of land surface processes in a global
-
PhD: Physics-informed AI-modelling of land surface processes Faculty: Faculty of Geosciences Department: Department of Physical Geography Hours per week: 36 to 40 Application deadline: 22
-
techniques); giving mathematical proofs of their correctness and efficiency; building state-of-the-art implementations of these new techniques (e.g., by leveraging data-parallel functional array programming
-
bioinformatic and AI tools to analyse the mass spectrometry data and improve the de novo sequencing workflows. Your work will lead to new antibody leads, that can be recombinantly produced and ultimately tested
-
; Process and interpret complex datasets to identify exposure patterns and determinants; Design and evaluate intervention strategies, including HEPA filtration and behavioural guidance; Collaborate with
-
Programme? Not funded by a EU programme Is the Job related to staff position within a Research Infrastructure? No Offer Description Are you fascinated by how nitrogen deposition and soil processes shape
-
encourage you to keep investing in your personal and professional development. For more information, please visit Working at Utrecht University . Selection process As Utrecht University, we want to be a home
-
research themes are Earth & Planetary Processes, Sustainable Use of the Subsurface, Planetary Health & Environment, and Climate & Life. The department hosts a highly international tenured staff. Besides the
-
-Fourier Transform Infrared Spectroscopy) for high-throughput particle identification; Process and interpret complex datasets to identify exposure patterns and determinants; Design and evaluate intervention
-
. To fully understand these developments, this project explores the processes underlying reading and reading education, and examines how recent advances in artificial intelligence, particularly generative AI