Sort by
Refine Your Search
-
Listed
-
Category
-
Country
- United States
- United Kingdom
- France
- Germany
- Portugal
- Sweden
- Netherlands
- Spain
- Norway
- Belgium
- Denmark
- Italy
- Singapore
- Australia
- Czech
- Morocco
- Finland
- Ireland
- Luxembourg
- Canada
- Switzerland
- Austria
- Poland
- China
- Romania
- United Arab Emirates
- Estonia
- Japan
- Brazil
- Hong Kong
- Andorra
- Vietnam
- Barbados
- Bulgaria
- Latvia
- Lithuania
- Malta
- Worldwide
- 28 more »
- « less
-
Program
-
Field
- Computer Science
- Engineering
- Medical Sciences
- Biology
- Economics
- Science
- Materials Science
- Mathematics
- Earth Sciences
- Chemistry
- Environment
- Business
- Humanities
- Psychology
- Linguistics
- Law
- Physics
- Arts and Literature
- Electrical Engineering
- Social Sciences
- Sports and Recreation
- Education
- Philosophy
- Statistics
- 14 more »
- « less
-
are developing methods and tools to explore and understand immunity across domains of life, from genomics to experimental work in various model organisms. The role of the engineer will be to consolidate, update
-
. We use advanced computational technologies to discover how biomolecules and organisms function and interact. We pioneer new methods for prediction, prevention, diagnostics and treatment of diseases
-
incorporate clinical, lifestyle, and nutritional factors to build predictive models through advanced bioinformatics and machine learning. By identifying molecular signatures that distinguish responders from non
-
hydrogenation, dehydrogenation, and hydrogen transfer reactions. Detailed characterization and kinetic studies will be performed to test computational predictions and microkinetic models, and to refine machine
-
identification, i.e. learning of models from measured data, and iii) real-time control, e.g. using the model predictive approach. We are working on several projects with industrial partners across the energy
-
Federated learning (FL) is an emerging machine learning paradium to enable distributed clients (e.g., mobile devices) to jointly train a machine learning model without pooling their raw data into a
-
Vitro to In Vivo Extrapolation of Toxicant Effects on Ovarian Function” and will focus on phthalates and developing models that extrapolate in vitro assay results to predict in vivo effects on ovarian
-
with a strong background in machine learning and LLMs, computer science, and modeling. The candidate will join the project “AI-driven predictive maintenance for buildings: Einar Mattsson (EM) - KTH
-
into the wave interaction and propagation processes. Modelling the propagation characteristics of optical communication systems with a focus on optical atmospheric turbulence and statistical prediction models
-
from semantic radio maps; learn which features act as reliable predictors of rewards or outcomes; associate these features with predictive models that guide decision-making; exploit such cue–outcome