Oracle Labs Internship

vor 1 Woche

Zurich, Schweiz Oracle Vollzeit

Oracle Labs Internship - Zurich - Global Graphs -22000BLN

**Applicants are required to read, write, and speak the following languages***: English

**Preferred Qualifications**

Intern with Domain Global Graphs

The Domain Global Graphs team at Oracle Labs, which focuses on machine learning and data/graph
analytics for enterprise domain data, has open internship positions available.
Oracle

Oracle, a global provider of enterprise cloud computing, is empowering businesses of all sizes on their journey of digital
transformation. Oracle Cloud provides leading-edge capabilities in software as a service, platform as a service, infrastructure
as a service, and data as a service.
- including artificial intelligence, machine learning, blockchain, and Internet of Things - in ways that create business
differentiation and advantage for customers. Continued technological advances are always on the horizon.

Oracle Labs

Oracle Labs is the advanced research and development arm of Oracle. We focus on the development of technologies that
keep Oracle at the forefront of the computer industry. Oracle Labs researchers look for novel approaches and
methodologies, often taking on projects with high risk or uncertainty, or that are difficult to tackle within a product
- development organization. Oracle Labs research is focused on real-world outcomes: our researchers aim to develop
technologies that will someday play a significant role in the evolution of technology and society. For example, chip
multithreading and the Java programming language grew out of work done in Oracle Labs.
Parallel Graph AnalytiX (PGX)

PGX [1] is a toolkit for graph analytics that supports graph algorithms, such as PageRank, graph
queries with PGQL (an SQL-like graph query language), and graph ML. PGX includes both a single
- machine in-memory engine and a distributed engine for extremely large graphs, and is already
available as an option in Oracle products and an active research project at Oracle Labs.

Oracle Labs Data Studio

Oracle Labs Data Studio is a web-based notebook platform for data scientists. By combining live code collaboration in
multiple programming languages with graph analytics and rich, interactive visualizations, it accelerates the process of
exploring and gaining insights from your data. For graph data, Data Studio comes packaged with PGX and PGQL, adding an
interactive visual layer that supports filtering graphs, highlighting elements, visualizing geographical data, and
expanding/contracting the view.

Domain Global Graphs

For enterprise use cases of PGX and Data Studio, organizations often adopts graph data model to integrate various data
sources into one global view from their enterprise domain (e.g., financial [2], retail or healthcare data), so that they can run
graph analytics and conduct investigations on them. The Domain Global Graph team helps with the integration of PGX and

Data Studio into solutions that support the investigation of domain global graphs, and helps with further research on how to
produce additional insight to facilitate investigation, e.g., by using ML techniques.

Internship Details

As part of your internship, you will be working with the Domain Global Graphs team
- for example by researching, designing and implementing new features, enhancing
existing functionality, measuring and improving performance, fixing bugs, etc. While
specific internship topics may change, here is a selection of current focus items.
Development and enhancement of machine learning and data analysis algorithms for

- Recognizing graph entities and their relationship from text and tables,

employing and improving techniques such as Natural Language Processing
(NLP), Named Entity Recognition (NER), Relation Extraction, and Co
- Reference Resolution.
- Generating a narrative text from a domain global graph, adapting them to

the graph structure.
- Improving global graph investigation, e.g., regarding financial patterns by

detecting similar or relevant subgraphs, or by automating the processing
and classification of cases under investigation, or with recommendation
techniques, or with imitation learning.
- Improving Entity Resolution (ER) techniques, e.g., by considering entities'

fields combinations and value thresholds, or by considering the graph
structure and properties of the resolved entities, with explainability and
Active Learning as well.
- Improving name and address parsing, standardization and matching, across

different languages as well.
Additional focus items, such as:

- Optimization of data pipeline for integrating data sources into graph model

and keeping the data synchronized.
- Ensuring data permission and lineage control for large-scale data

integration.
- Optimization and validation of data analysis pipeline and its deployment

with modern software architecture.
References
- labs/parallel-graph-analytix/overview/index.html
[2] Financial Crime and Compliance Studio,
- studio/

**Qualifications**:

**Require

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