Check out our new preprint, "Analyzing animal movement using deep learning" where we show that #DNN can replace step selection functions to adjust for nonlinearity, complex interactions, and inter-individual variability that can be extracted by #explainableAI with p-values: arxiv.org/pdf/2603.24009
Maximilian Pichler
Pra você que usa GLM/GLMMs, fique atento a problemas de dispersão!! E leia o preprint pra saber como testá-los! 🤓 /
For you that uses GLM/GLMMs, attention on dispersion problems! Read the preprint to know how to test for ir 🤓
Our new review article “Calibration, Sensitivity and Uncertainty Analysis of Complex Ecological Models—A Review” now online and freely available in #EcologyLetters dx.doi.org/10.1111/ele.... #Ecology #EcologicalModelling #SensitivityAnalysis #UncertaintyQuantification 🌐
Come work with us! 🪲For our new project bAImo we are searching for a PhD researcher combining modelling 💻 with ecological expertise, aiming to improve interdisciplinary approaches to insect monitoring 🔎🐝 please visit tinyurl.com/bAImo-PhDoffer for more details. Looking forward to your application 🦗😊
dx.doi.org
We provide a unified framework connecting sensitivity analysis, uncertainty analysis and model inversion or calibration, discuss their complementary roles in understanding and reducing uncertainty in....
#PhD position!
I’m looking for a PhD Student (1+3 years) to model insect populations using statistical models + deep learning at #TheoreticalEcology, Regensburg (Germany).
Join our team - please RT!
Details: karriere.uni-regensburg.de/tg7w9
#Insects #Ecology #DeepLearning #Ecology #Monitoring
Florian Hartig
Maximilian Pichler
We are hiring: 4 PhD Positions in Ecology / Data Science and one Ecological Data Scientist. For more information, see www.uni-regensburg.de/universitaet...
#PhDPosition in Ecological #DataScience in our group. For details, see www.uni-regensburg.de/universitaet... #MachineLearning #AI #DeepLearning #Statistics #Ecology #AcademicJobs
We are looking for a PhD student to join the AG Hartig (Theoretical Ecology) in the field of ecological data science / deep learning.