Sort by
Refine Your Search
-
Listed
-
Category
-
Country
- United States
- United Kingdom
- Norway
- Germany
- Sweden
- Netherlands
- Austria
- Belgium
- France
- Australia
- Spain
- Canada
- United Arab Emirates
- China
- Denmark
- Luxembourg
- Singapore
- Switzerland
- Brazil
- Hong Kong
- Czech
- Poland
- Greece
- India
- Portugal
- Estonia
- Finland
- Guinea
- Iceland
- Ireland
- Italy
- Lithuania
- Namibia
- New Zealand
- Romania
- 25 more »
- « less
-
Program
-
Field
- Computer Science
- Medical Sciences
- Biology
- Engineering
- Science
- Economics
- Mathematics
- Humanities
- Business
- Earth Sciences
- Environment
- Psychology
- Education
- Electrical Engineering
- Chemistry
- Social Sciences
- Linguistics
- Materials Science
- Arts and Literature
- Physics
- Philosophy
- Sports and Recreation
- 12 more »
- « less
-
reconstruction, quantitative image analysis, machine learning, or multimodal data fusion is highly desirable. Experience with neutron scattering or large-scale research facilities is beneficial. Self-motivated and
-
, astrophysical, and gravitational-wave observables; development of statistical-inference and machine-learning methods; direct analysis of current and future surveys or experiments. As members of the Arizona
-
-temporal-resolution bulk measurements (XAS, Raman spectroscopy, XRD), with particular emphasis on pair distribution function (PDF) analysis. Machine learning approaches will be used to support these analyses
-
analysis, or assistive technology; Experience in applying AI methods such as machine learning, deep learning, computer vision, multimodal data analysis and large language models (LLM) in health-related
-
the Hazards, Vulnerability and Resilience Institute (HVRI), Walker Institute of International and Area Studies, and the Center for GIScience and Geospatial Big Data. The Department offers PhD, MS, MA, BS, and
-
Droplet Sorting (FADS)—for the efficient phenotypic characterization and validation of massive enzyme libraries (>10^7 variants) Data-Driven Workflows: Closing the "Design-Build-Test-Learn" cycle by feeding
-
ties with the Faculty of Computing and Data Sciences, where shared interests in machine learning, large-scale data analytics, and Earth system modeling provide natural ground for joint advising, co
-
biological domains is a must PhD in computational biology, computer engineering, computer science, (bio)statistics, artificial intelligence, physics, or related. Desire to push the frontier
-
secondments and dedicated training activities. This post will have heavy emphasis on data science & ML programming applied to large environmental datasets (geospatial, weather, tide). This is an excellent
-
and predict how the immune system responds to interventions. This tight integration of advanced machine learning and experimental immunology allows us to tackle fundamental biological questions with