Sort by
Refine Your Search
-
Category
-
Country
-
Program
-
Field
-
learning, bioinformatics or advanced statistical methods, to help explore molecular, imaging, clinical and/or epidemiological data. You will apply, adapt and develop machine learning approaches to provide
-
-of-computing-science/ Project description and working tasks The project will develop privacy-aware machine learning (ML) models. We are interested in data-driven models for complex data, including high
-
or explainable AI or safety). Experience in machine learning, causal inference, image processing, human-robot interaction, or large language models. Experience in analyzing multimodal data (e.g., text, sensor
-
. Use advanced data processing services to perform bioinformatic analysis. Apply machine learning methods to complex sequencing and protein structure data. Qualifications You should have a minimum a high
-
. - Using statistics and machine learning to estimate model parameters based on travel surveys and other available statistics. - Studying how the location of workplaces, housing, and community services
-
Wiberg is “Innovative statistical and machine learning methods for comparing performance and outcome in register data studies”, with overall aim to develop, evaluate, and implement innovative statistical
-
multimodal machine learning. Admission requirements The general admission requirements for doctoral studies are a second- cycle level degree, or completed course requirements of at least 240 ECTS credits
-
to development projects. Establishing a research program in translational computational biology with a focus on developing new and scalable computational models (e.g. deep learning, machine learning, optimization
-
humans and society at large is either fully automated or heavily relies on automatically provided decision support. While machine learning approaches become increasingly prevalent in this context
-
multiplex analysis. We will assist the computer scientists to apply artificial intelligence Machine Deep Learning models using the omics data of mitophagy to predict risk of cancer and metastasis and design