15 bayesian-inference-tracking Postdoctoral research jobs at Technical University of Denmark
Sort by
Refine Your Search
-
. The ideal candidate for the position is a driven early-career scientist with a deep and genuine interest in seeking to better influence and complement chemical synthesis by inferring mechanistic details
-
machine learning for transport simulation. A core innovation involves Bayesian metamodeling techniques to construct fast surrogate models of the simulation space, enabling efficient scenario analysis
-
Communication, Singal Processing, Low Power Electronics, Wireless Sensing, Low-Power System Design, Machine Learning & Edge Inference, Underwater acoustic communication. Furthermore, you have a proven record of
-
by excellent grades in relevant courses from your education and a stellar track-record as an engineer/researcher as evidenced by your publications. You should have significant experience within several
-
candidate should have a proven track record of publishing in peer-reviewed international journals and possess excellent communication and academic writing skills in English. As a formal qualification, you
-
organisations and a successful track record of national and international research projects. You will have a close collaboration with the Food lab at DTU Skylab regarding the product development activities
-
carbohydrate chemistry. An interest in chemical biology and a desire to work in an interdisciplinary environment. A documented track record in the synthesis of complex oligosaccharides is an advantage
-
, e.g., demonstrated by a track-record of high-impact publications Previous work in inverse design / topology optimization We offer DTU is a leading technical university globally recognized
-
background is required with documented expertise in the following research areas: Expert understanding and ample track record of Mass Spectrometry-based proteomics Strong track record in both method
-
interest and documented skills and experience in using computer-based tools to analyse, simulate and predict capture performance of active and passive fishing gears. A track record of publishing in peer