Application deadline: 6th February 2022
GATE is a joint initiative between Sofia University “St. Kliment Ohridski”, Chalmers University of Technology, Sweden and Chalmers Industrial Technology, Sweden. The Swedish institutions are leading organizations in strategic initiatives such as AI Sweden, AI Research Centre, AI Innovation of Sweden and the Digital Twin Cities Centre.
GATE develops research capacity and potential in Big Data and Artificial Intelligence, cultivating the next generation of leading scientists by expanding the existing research network and establishing long-term agreements with leading global organizations. The Institute builds sustainable stakeholder relationships, focusing on technological collaboration between government, industry, academia and non-governmental organizations towards Artificial Intelligence and smart decision-making models.
We use artificial intelligence for a better and safer life.
Be part of the future and participate in applied research that develops innovations in the field of big data and artificial intelligence in collaboration with the scientific community, business and government.
For our research team we are looking for young at heart, motivated for high results and open to the unlimited possibilities of the future.
Experienced Researcher
Research area: Ontologies and Knowledge graphs
Nowadays Artificial Intelligence (AI) increasingly requires a strong integration of symbolic Knowledge Representation and Reasoning (e.g., ontologies, knowledge graphs, semantic web) and Machine Learning approaches. The key reason for this is that ML-based approaches expect or can be significantly improved by training them with high-quality and high-dimensional data. Building high-dimensional data, i.e., data that describe a certain phenomenon with a rich set of variables (rich data) is a difficult and effort-consuming task, especially when the quality needs to be preserved. It has estimated that up to 80% of the effort in data analytics projects is spent on preparing the data for the analytical modelling phase. Rich data is usually the result of the integration of data coming from different sources tackling semantic interoperability problems, such as the usage of different formats (e.g., CSVs vs. RDBs), different systems of identifiers (e.g., Place names vs. place identifiers), and different schemas (e.g., different attributes used to model the same domain).
Knowledge graphs have become the preferred abstraction to support data integration and solving semantic interoperability challenges, not only in the academy, but also in the public government domain (Linked Open Data initiatives) and in the industry (Google Knowledge Graph). Building knowledge graphs and enriching data using explicitly represented knowledge in symbolic form require addresses several research areas like data management, ontology engineering, semantic modelling, knowledge representation and logics. Despite a large number of technologies developed, a significant lack of efficient and effective solutions to the problems of data enrichment and semantic interoperability still exists, which prevents the development of AI applications on top of rich data.
We are looking for a mixture between a scientist, engineer and philosopher who can create and maintain complex Knowledge graphs that amalgamate multiple data sources to represent complex entities in the GATE application domains: Future Cities, Digital Health, Smart Industry and Intelligent Government. Our projects take many forms and require a diverse and flexible skillset that let you solve complex data integration and analytical issues quickly and proficiently.
Your responsibilities:
- Design, implement and maintain complex Linked Data models;
- Uncover data and their relationships from a variety of sources: relational databases, flat files and RDF documents, other;
- Provide efficient data integration in GATE application domains;
- Create and instantiate OWL ontologies to expose semantics encoded in the data;
- Construct and maintain ETL pipelines to keep Linked Data resources up to date from various sources;
- Scientific paper writing;
- Keep up-to-date with latest technology trends;
- Engage in appropriate training and development opportunities;
- Participate in educational programs in the field of ontologies and knowledge graphs;
- Participate in generating ideas for applying the results of scientific work in innovative projects;
- You are engaged in continuous professional development and participate in training and knowledge exchange events;
- Prepare presentations to promote research results at national and international level.
Requirements:
- PhD Degree in computer science, applied mathematics, engineering or a related field. Alternatively, a Master's Degree in the same areas plus a minimum of 4 years of relevant experience in industry or academia;
- Expertise with two or more of the following technologies Graph and Semantic technologies such as Neo4J, Graph DB / Triple Stores like Stardog, NoSQL DBs, SPARQL, Cypher, Gremlin, Protégé, RDF, OWL, R2RML;
- Familiarity with graph Analytics & Inferencing / Visualization tools such as Cytoscape, Cytoscape js, Gephi, GraphViz, Neovis.js and especially related to GIS: Leaflet.js, Folium and similar;
- Knowledge of and experience in implementing Object Oriented design and experience in at least one programming language like Java, Scala, C++, C# or similar and at least one scripting language such as Python or R;
- Experience or familiarity with AI and Machine learning concepts: Supervised and Unsupervised machine learning, Neural Networks, Support vector machines, Kernel methods;
- Experience in working with Jupyter notebook/Jupyter lab and other tools for reproducible research;
- Experience in domains where knowledge graphs can be applied like GIS, Bioinformatics and Health;
- Solid oral/written communication and presentation skills in order to explain the outcome of research (and value thereof) to coworkers and peers;
- Ability to prioritize tasks and work on multiple assignments, and a deep desire to find ways to create value and deliver results;
- Fluent English is a must.
Our offer:
- You will have the freedom to conduct research in any area within the scope and priorities of GATE, creating new visions for the future
- You will be provided with numerous opportunities for learning, knowledge exchange and career development, locally and internationally
- Your research will be supported by an advanced research infrastructure, comprising of the GATE platform and Open Innovation Labs
- You will have a flexible work schedule and, modern and appealing work environment, stirring up creativity and productivity
- Competitive working conditions and a salary commensurate with your skills and experience
How to apply:
Please send your contact data and files with personal documents on our Application Form - Gate (gate-ai.eu) till February 6th 2022:
- Cover/motivation letter that explains the motivating factors for considering the position (max. 1 pp),
- CV with complete publication list,
- Copies of diplomas for completed education and certificates of qualification,
- Copies of documents certifying past work experience in the relevant field,
- Brief description of important scientific achievements and scientific outlook (max. 2 pp),
- Two references letters or personal recommendations, arranged by applicants and directly submitted by the letter or provided as contact data in the cover letter,
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As an attachment to your application please sign and enclose the following declaration:
I agree to the processing of my personal data included in this application for the needs necessary to carry out the recruitment.
Stages of the contest:
1.The Selection Committee reviews the documents, submitted by the candidates and selects those meeting the requirements of the job, as described in the job profile. The selected candidates will be informed by 6 February 2022.
2.Online interviews will be held with the selected applicants in the period 7 – 18 February 2022.
3.All interviewed candidates will be notified in writing.
4.The successful candidate will be offered a labour contract under the project BG05M2OP001-1.003-0002-C01 „Big Data for Smart Society”.
Additional information on the site www.gate-ai.eu or contact us on: dessislava.petrova@gate-ai.eu
By applying for these positions, you voluntarily provide your personal data and consent to be processed for the purpose of recruitment and selection of personnel. The processing of your personal data shall be carried out in accordance with the requirements of Regulation (EU) 2016/679 (General Data Protection Regulation), the Personal Data Protection Law and related legal acts in Bulgaria.