Sort by
Refine Your Search
-
Listed
-
Category
-
Country
-
Field
-
practices in different research communities; Teach lessons and workshops such as data processing and analysis using R or Python, tools and best practices for data management, computational best practices
-
simulations, statistical mechanics, computer programming (e.g., C++, Python), polymer theory, molecular modeling (e.g., of proteins, nucleic acids, ligands), coarse-grain and polymer model development
-
or soon after Advanced training in econometrics, empirical archival methods, and causal inference methods Strong programming skills in Stata, SAS, R, Python, or similar software Experience in teaching
-
Post Doctoral Researcher in Human-Centered AI for Software Engineering, Department of Electrical ...
particular with Large Language Models. Solid programming expertise in Python. Be the main author in at least one journal publication in the area of AI4SE, published at a high impact journal. Experience with
-
construed as an exhaustive list of all job duties performed by the personnel so classified. Management reserves the right to revise or amend duties at any time. Required Qualifications Education: Ph.D., M.D
-
, United States of America [map ] Subject Areas: Climate Science Atmospheric Sciences Quantitative Analysis Appl Deadline: (posted 2025/05/12, listed until 2025/06/23) Position Description: Apply Today is the last day you can
-
programming in, for example, R or Python. Particularly valuable is a research background in ecology, biodiversity, systems biology, or related areas, as well as experience working with time-series data, dynamic
-
and data management tools, such as Python, R, Jupyter, Linux, Globus, STAC, GitHub, containers is recommended. Familiarity with cloud technologies, databases and Pangeo ecosystems is a bonus. The Term
-
language processing. Experience with transformer-based architectures (e.g., BERT, GPT) is highly desirable. Proficiency in Python and relevant machine learning libraries (e.g., TensorFlow, PyTorch). Experience with
-
by relevant publications and research projects. Technical Skills: Proficiency in modeling and simulation methods for energy networks. Experience with energy network analysis tools (e.g., MATLAB, Python