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About Xebia For more than 25 years, our global network of passionate technologists and pioneering craftspeople has delivered cutting-edge technology and game-changing consulting to companies on the brink of AI driven digital transformation. Since 2001, we have grown into a full service digital consulting company with 6000+ professionals working on a worldwide ambition. Driven by the desire to make a difference, we keep innovating. Fuelling the growth of our company with our knowledge worker culture. When teaming up with Xebia, expect in-depth expertise based on an authentic, value-led, and high quality way of working that inspires all we do. At Xebia, we put ‘People First’—committed to attracting diverse talent and fostering an inclusive, respectful workplace where everyone is valued for their contributions. We welcome all individuals and evaluate solely on the quality of their work and teamwork. About the Role Scientific Knowledge Engineer, Ontology & Data Modeling This role is responsible for maximizing the value of our data assets over a lifetime to bring purpose to data by acting as translators of highly technical information from domain experts into an appropriate data model – complete with significant ontology and vocabulary - that can be utilized to effectively structure and index the data. Specifically working with Product managers and R&D subject matter expertise to define the language (data models, ontology, standards, etc.) of science into data products by acting as the voice of “Knowledge base” and interoperability/value of asset. Key responsibilities include: • Definition of schemas/ontology and data models of scientific information required for the creation of value adding data products. This includes accountability for the quality control and mapping specifications to be industrialized by data engineering and maintained in platform provisioned tooling., • Accountable for the quality control (through validation and verification) of mapping specifications to be industrialized by data engineering and maintained in platform provisioned tooling – e.g., models, schemas, controlled vocab., • Working with Product managers/engineers confidently convert business need into defined deliverable business requirements to enable the integration of large-scale biology data to predict, model, and stabilize therapeutically relevant protein complex and antigen conformations for drug and vaccine discovery., • Collaborate with external groups to align data standards with industry/ academic ontologies ensuring that data standards are defined with usage/analytics in mind., • Provides bespoke subject matter expertise for R&D data to translate deep science into data for actionable insights, • Contribute to and maintain documentation of data standards, ontology decisions, and mapping rationale to support organizational knowledge transfer and auditability Basic Qualifications: We are looking for professionals with these required skills to achieve our goals: • Masters degree in Bioinformatics, Biomedical Science, Biomedical Engineering, Molecular Biology, or Computer Science (with a life science application focus), • 6+ years of relevant work experience, • Specific experience contributing to Knowledge Graph development efforts, including entity modeling, relationship design, and schema governance, • Hands-on experience with open-source ontology tools and languages: Protégé, SPARQL, OWL, SKOS, SHACL, RML, RDF/Turtle, • Working knowledge of major life sciences ontologies: Gene Ontology (GO), OBO Foundry ontologies (CL, UBERON, HPO, MONDO, CHEBI, EFO, CLO), MeSH, SNOMED CT, UMLS, • Familiarity with linked data principles and semantic web technologies, • Experience with industry-standard tools for building data serialization protocols (e.g., JSON Schema, LinkML), • Proficiency in at least one programming language — preferably Python — for scripting vocabulary mappings, building data models, automating QC, and prototyping pipelines Preferred Qualifications: If you have the following characteristics, it would be a plus: • Experience with data governance and data quality tooling (e.g., Ataccama, Informatica, Talend, OpenRefine, Great Expectations, dbt), • Experience with at least one programming language – e.g. Python – for scripting vocabulary mappings, building data models, etc, • Experience supporting LLM integration or AI-readiness workflows — including metadata enrichment, entity linking, embedding pipelines, or retrieval-augmented generation (RAG) architectures, • Understanding of vector databases and their role in semantic search and knowledge retrieval (e.g., Weaviate, Chroma), • Familiarity with cloud data platforms and infrastructure relevant to large-scale biological data (e.g., AWS, GCP, Azure), • Familiarity with graph database technologies (e.g., Neo4j, Amazon Neptune, Stardog, GraphDB, TigerGraph) Compensation Salary Range: €58,000 – €68,000 gross per year, depending on experience, skills, and overall fit for the role.

About Xebia For more than 25 years, our global network of passionate technologists and pioneering craftspeople has delivered cutting-edge technology and game-changing consulting to companies on the brink of AI driven digital transformation. Since 2001, we have grown into a full service digital consulting company with 6000+ professionals working on a worldwide ambition. Driven by the desire to make a difference, we keep innovating. Fuelling the growth of our company with our knowledge worker culture. When teaming up with Xebia, expect in-depth expertise based on an authentic, value-led, and high quality way of working that inspires all we do. At Xebia, we put ‘People First’—committed to attracting diverse talent and fostering an inclusive, respectful workplace where everyone is valued for their contributions. We welcome all individuals and evaluate solely on the quality of their work and teamwork. About the Role Scientific Knowledge Engineer, Ontology & Data Modeling This role is responsible for maximizing the value of our data assets over a lifetime to bring purpose to data by acting as translators of highly technical information from domain experts into an appropriate data model – complete with significant ontology and vocabulary - that can be utilized to effectively structure and index the data. Specifically working with Product managers and R&D subject matter expertise to define the language (data models, ontology, standards, etc.) of science into data products by acting as the voice of “Knowledge base” and interoperability/value of asset. Key responsibilities include: • Definition of schemas/ontology and data models of scientific information required for the creation of value adding data products. This includes accountability for the quality control and mapping specifications to be industrialized by data engineering and maintained in platform provisioned tooling., • Accountable for the quality control (through validation and verification) of mapping specifications to be industrialized by data engineering and maintained in platform provisioned tooling – e.g., models, schemas, controlled vocab., • Working with Product managers/engineers confidently convert business need into defined deliverable business requirements to enable the integration of large-scale biology data to predict, model, and stabilize therapeutically relevant protein complex and antigen conformations for drug and vaccine discovery., • Collaborate with external groups to align data standards with industry/ academic ontologies ensuring that data standards are defined with usage/analytics in mind., • Provides bespoke subject matter expertise for R&D data to translate deep science into data for actionable insights, • Contribute to and maintain documentation of data standards, ontology decisions, and mapping rationale to support organizational knowledge transfer and auditability Basic Qualifications: We are looking for professionals with these required skills to achieve our goals: • Masters degree in Bioinformatics, Biomedical Science, Biomedical Engineering, Molecular Biology, or Computer Science (with a life science application focus), • 6+ years of relevant work experience, • Specific experience contributing to Knowledge Graph development efforts, including entity modeling, relationship design, and schema governance, • Hands-on experience with open-source ontology tools and languages: Protégé, SPARQL, OWL, SKOS, SHACL, RML, RDF/Turtle, • Working knowledge of major life sciences ontologies: Gene Ontology (GO), OBO Foundry ontologies (CL, UBERON, HPO, MONDO, CHEBI, EFO, CLO), MeSH, SNOMED CT, UMLS, • Familiarity with linked data principles and semantic web technologies, • Experience with industry-standard tools for building data serialization protocols (e.g., JSON Schema, LinkML), • Proficiency in at least one programming language — preferably Python — for scripting vocabulary mappings, building data models, automating QC, and prototyping pipelines Preferred Qualifications: If you have the following characteristics, it would be a plus: • Experience with data governance and data quality tooling (e.g., Ataccama, Informatica, Talend, OpenRefine, Great Expectations, dbt), • Experience with at least one programming language – e.g. Python – for scripting vocabulary mappings, building data models, etc, • Experience supporting LLM integration or AI-readiness workflows — including metadata enrichment, entity linking, embedding pipelines, or retrieval-augmented generation (RAG) architectures, • Understanding of vector databases and their role in semantic search and knowledge retrieval (e.g., Weaviate, Chroma), • Familiarity with cloud data platforms and infrastructure relevant to large-scale biological data (e.g., AWS, GCP, Azure), • Familiarity with graph database technologies (e.g., Neo4j, Amazon Neptune, Stardog, GraphDB, TigerGraph) Compensation Salary Range: €58,000 – €68,000 gross per year, depending on experience, skills, and overall fit for the role.

About Xebia For more than 25 years, our global network of passionate technologists and pioneering craftspeople has delivered cutting-edge technology and game-changing consulting to companies on the brink of AI driven digital transformation. Since 2001, we have grown into a full service digital consulting company with 6000+ professionals working on a worldwide ambition. Driven by the desire to make a difference, we keep innovating. Fuelling the growth of our company with our knowledge worker culture. When teaming up with Xebia, expect in-depth expertise based on an authentic, value-led, and high quality way of working that inspires all we do. At Xebia, we put ‘People First’—committed to attracting diverse talent and fostering an inclusive, respectful workplace where everyone is valued for their contributions. We welcome all individuals and evaluate solely on the quality of their work and teamwork. About the Role Scientific Knowledge Engineer, Ontology & Data Modeling This role is responsible for maximizing the value of our data assets over a lifetime to bring purpose to data by acting as translators of highly technical information from domain experts into an appropriate data model – complete with significant ontology and vocabulary - that can be utilized to effectively structure and index the data. Specifically working with Product managers and R&D subject matter expertise to define the language (data models, ontology, standards, etc.) of science into data products by acting as the voice of “Knowledge base” and interoperability/value of asset. Key responsibilities include: • Definition of schemas/ontology and data models of scientific information required for the creation of value adding data products. This includes accountability for the quality control and mapping specifications to be industrialized by data engineering and maintained in platform provisioned tooling., • Accountable for the quality control (through validation and verification) of mapping specifications to be industrialized by data engineering and maintained in platform provisioned tooling – e.g., models, schemas, controlled vocab., • Working with Product managers/engineers confidently convert business need into defined deliverable business requirements to enable the integration of large-scale biology data to predict, model, and stabilize therapeutically relevant protein complex and antigen conformations for drug and vaccine discovery., • Collaborate with external groups to align data standards with industry/ academic ontologies ensuring that data standards are defined with usage/analytics in mind., • Provides bespoke subject matter expertise for R&D data to translate deep science into data for actionable insights, • Contribute to and maintain documentation of data standards, ontology decisions, and mapping rationale to support organizational knowledge transfer and auditability Basic Qualifications: We are looking for professionals with these required skills to achieve our goals: • Masters degree in Bioinformatics, Biomedical Science, Biomedical Engineering, Molecular Biology, or Computer Science (with a life science application focus), • 6+ years of relevant work experience, • Specific experience contributing to Knowledge Graph development efforts, including entity modeling, relationship design, and schema governance, • Hands-on experience with open-source ontology tools and languages: Protégé, SPARQL, OWL, SKOS, SHACL, RML, RDF/Turtle, • Working knowledge of major life sciences ontologies: Gene Ontology (GO), OBO Foundry ontologies (CL, UBERON, HPO, MONDO, CHEBI, EFO, CLO), MeSH, SNOMED CT, UMLS, • Familiarity with linked data principles and semantic web technologies, • Experience with industry-standard tools for building data serialization protocols (e.g., JSON Schema, LinkML), • Proficiency in at least one programming language — preferably Python — for scripting vocabulary mappings, building data models, automating QC, and prototyping pipelines Preferred Qualifications: If you have the following characteristics, it would be a plus: • Experience with data governance and data quality tooling (e.g., Ataccama, Informatica, Talend, OpenRefine, Great Expectations, dbt), • Experience with at least one programming language – e.g. Python – for scripting vocabulary mappings, building data models, etc, • Experience supporting LLM integration or AI-readiness workflows — including metadata enrichment, entity linking, embedding pipelines, or retrieval-augmented generation (RAG) architectures, • Understanding of vector databases and their role in semantic search and knowledge retrieval (e.g., Weaviate, Chroma), • Familiarity with cloud data platforms and infrastructure relevant to large-scale biological data (e.g., AWS, GCP, Azure), • Familiarity with graph database technologies (e.g., Neo4j, Amazon Neptune, Stardog, GraphDB, TigerGraph) Compensation Salary Range: €58,000 – €68,000 gross per year, depending on experience, skills, and overall fit for the role.

As a Computer Vision Engineer, you will take on the following responsibilities and challenges: • Machine Learning: Design and develop reliable, scalable, and efficient machine learning models for object detection, segmentation, and classification tasks., • Algorithms: Research, implement, and optimize computer vision and numerical algorithms to build new system components or enhance existing ones., • Software Development: Build a broad range of computer vision software systems, from production-ready microservices to rapid prototypes that integrate multiple components., • Data Analysis: Apply statistical methods and use visualization tools to develop dashboards that monitor and evaluate both component performance and production systems., • Innovative Development (“Vibe Coding”): Leverage creative, interdisciplinary approaches to develop innovative solutions that remain robust, maintainable, and aligned with software engineering best practices. We work in small teams with a startup mentality. We are a horizontal organization where originality and self-drive are valuable assets that we encourage. Our team members have diverse research and technical backgrounds in various complementary fields. You will have a key position in designing and building innovative products. Our clients are the largest lumber sawmills worldwide. These companies play a key role in the transition to a carbon-neutral world, and we help them bring innovation, technology, and automation to drive efficiency and reduce waste. A typical candidate would • have experience in Classical Computer Vision and Machine Learning, • have experience building software, • have experience with vibe coding, • draw data-driven conclusions using statistical inference, • have programming experience in Python and Java, • be self-driven and able to independently carry a task to completion, • be pragmatic and goal-oriented The ideal candidate would • have an advanced understanding of deep learning and computer vision methods, • have developed and maintained production software solutions, • have 3-year experience in a R&D position in the industry, • enjoy reading the latest academic papers in the field, • thrive in a client-driven research environment that requires creative interdisciplinary solutions Benefits • training, knowledge transfer sessions, and courses, • regular activities with the team, team building, • casual & friendly working environment with opportunities to impact the company with your ideas and involvement, • flexible working hours, • bonuses and attractive salary package, • working in an international/multicultural team, • support for exams and certifications for professional growth, • smart people all around, and real technical challenges, • extra perks (Between 21 and 25 vacation days, days off for special or unexpected events) Ready to Apply? We're excited to hear from you! Send us your application and let's start the conversation about your future with us.

As a Computer Vision Engineer, you will take on the following responsibilities and challenges: • Machine Learning: Design and develop reliable, scalable, and efficient machine learning models for object detection, segmentation, and classification tasks., • Algorithms: Research, implement, and optimize computer vision and numerical algorithms to build new system components or enhance existing ones., • Software Development: Build a broad range of computer vision software systems, from production-ready microservices to rapid prototypes that integrate multiple components., • Data Analysis: Apply statistical methods and use visualization tools to develop dashboards that monitor and evaluate both component performance and production systems., • Innovative Development (“Vibe Coding”): Leverage creative, interdisciplinary approaches to develop innovative solutions that remain robust, maintainable, and aligned with software engineering best practices. We work in small teams with a startup mentality. We are a horizontal organization where originality and self-drive are valuable assets that we encourage. Our team members have diverse research and technical backgrounds in various complementary fields. You will have a key position in designing and building innovative products. Our clients are the largest lumber sawmills worldwide. These companies play a key role in the transition to a carbon-neutral world, and we help them bring innovation, technology, and automation to drive efficiency and reduce waste. A typical candidate would • have experience in Classical Computer Vision and Machine Learning, • have experience building software, • have experience with vibe coding, • draw data-driven conclusions using statistical inference, • have programming experience in Python and Java, • be self-driven and able to independently carry a task to completion, • be pragmatic and goal-oriented The ideal candidate would • have an advanced understanding of deep learning and computer vision methods, • have developed and maintained production software solutions, • have 3-year experience in a R&D position in the industry, • enjoy reading the latest academic papers in the field, • thrive in a client-driven research environment that requires creative interdisciplinary solutions Benefits • training, knowledge transfer sessions, and courses, • regular activities with the team, team building, • casual & friendly working environment with opportunities to impact the company with your ideas and involvement, • flexible working hours, • bonuses and attractive salary package, • working in an international/multicultural team, • support for exams and certifications for professional growth, • smart people all around, and real technical challenges, • extra perks (Between 21 and 25 vacation days, days off for special or unexpected events) Ready to Apply? We're excited to hear from you! Send us your application and let's start the conversation about your future with us.

As a Computer Vision Engineer, you will take on the following responsibilities and challenges: • Machine Learning: Design and develop reliable, scalable, and efficient machine learning models for object detection, segmentation, and classification tasks., • Algorithms: Research, implement, and optimize computer vision and numerical algorithms to build new system components or enhance existing ones., • Software Development: Build a broad range of computer vision software systems, from production-ready microservices to rapid prototypes that integrate multiple components., • Data Analysis: Apply statistical methods and use visualization tools to develop dashboards that monitor and evaluate both component performance and production systems., • Innovative Development (“Vibe Coding”): Leverage creative, interdisciplinary approaches to develop innovative solutions that remain robust, maintainable, and aligned with software engineering best practices. We work in small teams with a startup mentality. We are a horizontal organization where originality and self-drive are valuable assets that we encourage. Our team members have diverse research and technical backgrounds in various complementary fields. You will have a key position in designing and building innovative products. Our clients are the largest lumber sawmills worldwide. These companies play a key role in the transition to a carbon-neutral world, and we help them bring innovation, technology, and automation to drive efficiency and reduce waste. A typical candidate would • have experience in Classical Computer Vision and Machine Learning, • have experience building software, • have experience with vibe coding, • draw data-driven conclusions using statistical inference, • have programming experience in Python and Java, • be self-driven and able to independently carry a task to completion, • be pragmatic and goal-oriented The ideal candidate would • have an advanced understanding of deep learning and computer vision methods, • have developed and maintained production software solutions, • have 3-year experience in a R&D position in the industry, • enjoy reading the latest academic papers in the field, • thrive in a client-driven research environment that requires creative interdisciplinary solutions Benefits • training, knowledge transfer sessions, and courses, • regular activities with the team, team building, • casual & friendly working environment with opportunities to impact the company with your ideas and involvement, • flexible working hours, • bonuses and attractive salary package, • working in an international/multicultural team, • support for exams and certifications for professional growth, • smart people all around, and real technical challenges, • extra perks (Between 21 and 25 vacation days, days off for special or unexpected events) Ready to Apply? We're excited to hear from you! Send us your application and let's start the conversation about your future with us.

Temporal Transfer busca un PERSONAL TÉCNICO DE ELABORACIÓN para su empresa en ULLDECONA, especializada en productos de cuidado personal.

Empresa líder en el sector siderometalúrgico busca incorporar personal especializado en SOLDADURA, con experiência demostrable, para su planta ubicada en Ulldecona.Interpretación y lectura de planos técnicos.Soldadura de piezas y estructuras metálicas.Verificación y control de la calidad del