Sort by
Refine Your Search
-
Listed
-
Category
-
Country
- United States
- United Kingdom
- Sweden
- Germany
- France
- Norway
- Portugal
- Singapore
- Belgium
- Spain
- Denmark
- Netherlands
- China
- Italy
- Switzerland
- Canada
- Luxembourg
- Australia
- United Arab Emirates
- Hong Kong
- Austria
- Finland
- Ireland
- Poland
- Czech
- Cyprus
- Japan
- Morocco
- Brazil
- Latvia
- India
- Estonia
- Saudi Arabia
- Lithuania
- South Africa
- Bulgaria
- Greece
- Romania
- Taiwan
- Andorra
- Israel
- Slovenia
- Armenia
- Barbados
- Europe
- Iceland
- Malta
- Mexico
- New Zealand
- Slovakia
- Vietnam
- 41 more »
- « less
-
Program
-
Field
- Computer Science
- Medical Sciences
- Economics
- Engineering
- Biology
- Science
- Business
- Mathematics
- Education
- Psychology
- Materials Science
- Arts and Literature
- Humanities
- Chemistry
- Social Sciences
- Linguistics
- Earth Sciences
- Environment
- Law
- Sports and Recreation
- Electrical Engineering
- Physics
- Design
- Philosophy
- 14 more »
- « less
-
or equivalent Skills/Qualifications The work and responsibilities of the researcher will include the following research topics: Knowledge in: Computational neuroscience Machine learning / AI Biomedical data
-
records, aiming to co-create practical tools deployable in real-world clinical settings. This work is central to a multidisciplinary collaboration bringing together experts in machine learning, neuroscience
-
robust data pipelines, creating efficient machine learning models, and integrating AI capabilities into existing systems to improve efficiency, accuracy, and service quality while reducing operational
-
Lexington, KY Grade Level 47 Salary Range $57,158-94,286/year Type of Position Staff Position Time Status Full-Time Required Education BA Click here for more information about equivalencies: https
-
. Experience with Python programming. Familiarity with machine learning methods. Strong communication skills and ability to work collaboratively across theory and experiment. Desired Qualifications PhD in
-
psychoactive substances, in seized drug products or clinical samples. The candidate will have the opportunity to work directly with experimentalists to validate predictions made by their machine-learning models
-
leverage state of the art machine learning models (AlphaFold2, RFdiffusion) and multi-omics data integration to guide the rational design and optimization of therapeutic antibodies. Overall, you will have
-
records of experiments and outcomes. General computer skills and ability to quickly learn and master computer programs, databases, and scientific applications. Ability to work under deadlines with general
-
, organised researcher who can evidence: A PhD, or equivalent in statistics, machine learning or a closely related discipline, OR near to completion of a PhD. Expert knowledge of statistical inference methods
-
the following is desired: - Agentic and sequential decision-making for autonomous experimentation, including active learning and optimal experimental design - Generative and probabilistic modeling