Sort by
Refine Your Search
-
Category
-
Country
-
Program
-
Employer
- University of Arkansas
- New England HERC
- XIAN JIAOTONG LIVERPOOL UNIVERSITY (XJTLU)
- Brown University
- Centre for Genomic Regulation
- Eindhoven University of Technology (TU/e)
- Instituto de Sistemas e Robótica (ISR)
- Northeastern University
- Pennsylvania State University
- Rutgers University
- Technical University of Munich
- University of British Columbia
- University of Pittsburgh
- 3 more »
- « less
-
Field
-
for graph drawing problems Design and analysis of efficient algorithms for hypergraph visualization Computational complexity of graph and hypergraph embedding problems Combinatorial properties and
-
pipelines in MATLAB , Python, R, or similar platforms for electrophysiology processing, network analysis, visualization, quality control, and statistical analysis. Perform and analyze electrical
-
transcriptomics). The candidate will design and apply integrative data analysis (computational/statistical/causal) and visualization techniques for multi-omic data to address research hypotheses. The
-
data, beyond routine application of existing analysis pipelines. · Hands-on experience with graph neural networks or perturbation modeling. · Experience integrating omics data with clinical data
-
, VADER, and transformer-based models (e.g., BERT, GPT); Familiar with social network analysis (SNA) using NetworkX, igraph, and Gephi for complex network and graph-based data exploration
-
; Specialized in NLP, text mining, and graph analytics, including the use of NLTK, spaCy, TextBlob, VADER, and transformer-based models (e.g., BERT, GPT); Familiar with social network analysis (SNA) using
-
Eindhoven University of Technology (TU/e) | Eindhoven, Provincie Noord-Brabant | Netherlands | about 1 month ago
that focuses on algorithms research. The cluster is known for its research in computational geometry and topology, algorithms for spatiotemporal data, and algorithmic visualization, as well as graph and
-
, VADER, and transformer-based models (e.g., BERT, GPT); Expert in social network analysis (SNA) using NetworkX, igraph, and Gephi for complex network and graph-based data exploration; Successful
-
, TextBlob, VADER, and transformer-based models (e.g., BERT, GPT); Familiar with social network analysis (SNA) using NetworkX, igraph, and Gephi for complex network and graph-based data exploration
-
automations. Familiarity with data analysis and visualization tools such as Tableau or Cognos Analytics. Familiarity with at least one programming language and an interest in growing software development