Sort by
Refine Your Search
-
Category
-
Country
-
Program
-
Employer
- Aalborg University
- Aarhus University
- Aalborg Universitet
- University of Copenhagen
- Aarhus University (AU)
- Copenhagen Business School
- King's College London
- Technical University of Denmark (DTU)
- Technical University of Denmark;
- TEGNOLOGY APS
- Technical University Of Denmark
- Technical University of Denmark
- 2 more »
- « less
-
Field
-
statistics, AI and machine learning methods, including demonstrated experience in analysing multiple global change drivers, e.g. land use intensity, climate change, nitrogen deposition. Proven capability
-
analysis, causal inference with machine learning, and deep learning for various health-related domains. The Global Pathogen Analysis Platform (GPAP) is a new international initiative to strengthen global
-
for translatome analysis Expertise in integrating large-scale multiomic datasets, including machine learning based approaches Excellent written communication skills demonstrated by an outstanding publication track
-
seek a PhD candidate to work on representation learning methods on graphs for modeling static and temporal networks, with applications to ecological systems and beyond. The project will focus
-
• Participate in the department’s research environment • Complete a PhD training programme • Teach at one or more of the department programmes Your main task as a PhD student will be to develop and complete a PhD
-
the development of new research directions at the department. Your competencies You hold a PhD degree in Electrical Engineering, Control Engineering, Electrochemistry or a closely related field or can document
-
, cryo-electron microscopy (cryo-EM), cryo-EM-based polyclonal serology (cryo-EMPEM), molecular dynamics simulations, machine learning, and structural biology to define epitopes and engineer improved
-
technologies Development and utilization of high throughput methods for characterizing and quantifying the physicochemical behavior of food macromolecules in complex matrices. Modelling and the use of machine
-
methodological development and application of bioinformatics, biostatistics, machine learning, and data management within clinical research. CLINDA is interdisciplinary and employs biostatisticians
-
implement a hyperspectral imaging system tailored to bulk forensic trace analysis and develop chemometric and machine-learning models for material identification and classification. You will evaluate