Sort by
Refine Your Search
-
Employer
-
Field
-
Postdoctoral Researcher in Natural Language Processing and Digital Humanities (18 months, full-time)
with word embeddings, semantic modelling, and/or network analysis Ability to work independently as well as collaboratively in an interdisciplinary environment Excellent written and spoken English
-
biochemistry. Expertise in e.g. CRISPR-mediated gene editing, protein structure prediction, mass spectrometry-based proteomics, or fluorescence microscopy. Expertise and interest in functional analysis
-
available in the Nielsen Lab, which focuses on understanding how post-translational modifications (PTMs) such as ADP-ribosylation networks regulate proteome states and cellular function. The position is
-
network. Organize data analysis, write reports and manuscripts, and create visualizations to summarize findings. Presenting results orally to a broad audience. Occasional travel may be required. Required
-
Discovery Innovation Network foundation, NNF grant number: NNF23SA0088590. The position focuses on experimental development at the interface of microfluidic organ-on-chip systems and metabolic magnetic
-
be used to prepare lamella samples for high resolution cryo-EM imaging and tomography. From AI assisted image analysis, 3D models for key proteins and biomolecular complexes will be fitted into 3D
-
) as well as various other algorithmic methods for data processing and analysis. Current projects within this scope include, but are not limited to: Detection and classification of lesions Segmentation
-
: June 1st, 2026. Job Description The position is part of SDU LCE’s strategic research agenda on net-zero energy systems, carbon management, and CCUS infrastructure development. The postdoc will lead
-
that are difficult to capture through art historical analysis or qualitative methods alone. Art practices engage creatively with embodied memory and material remnants of colonial history, opening new possibilities
-
modelling of cooling systems at building or district scale and that you are familiar with methods for performance evaluation of district cooling networks. Experience with techno-economic analysis of district