44 big-data Postdoctoral positions at Stony Brook University in Ireland-University-Ranking-2024
Sort by
Refine Your Search
-
extreme weather forecasting, employing data science models as developed in computer vision and natural language processing (NLP). This project leverages the large-scale high-performance computing (HPC
-
interiors. This work will rely on large-scale atomistic simulations paired with machine-learning interatomic potentials. Duties: ● The postdoc will generate density functional theory reference data, use
-
., Python). * Record of managing and analyzing large-scale genomics or population genetics datasets. * Demonstrated ability and willingness to work both independently and collaboratively. * Ability and
-
scripting language (e.g., Python). ● Record of managing and analyzing large-scale genomics or population genetics datasets. ● Demonstrated ability and willingness to work both independently and
-
scripting language (e.g., Python). ● Record of managing and analyzing large-scale genomics or population genetics datasets. ● Demonstrated ability and willingness to work both independently and
-
that demonstrate high potential for research impact. AI Innovation Postdoctoral Scholars: The AI Innovation Institute (AI3) at Stony Brook University invites candidates for a large cohort of fully-funded
-
techniques. ● Proficiency in instrument control, data acquisition, and data analysis using tools such as LabView, Python or MATLAB. ● A record of peer-reviewed publications and demonstrated ability
-
and evolutionary biology or a closely related field. Experience with computational analysis. Experience in assembling and analyzing short-read data (e.g., Illumina) or long-read data (e.g., Oxford
-
methodology, conduct research experiments in the field of Multimodal aerial/underwater robotics. ● Collect and analyze data, including periodical/literature search and utilizing specialized skills in
-
Equation, Stochastic simulation algorithms, and approximation methods. ● Experience with single-cell or spatial transcriptomic data analysis. ● Familiarity with machine learning and deep learning