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0Universidade da Coruña
Murcia, ES
Research Support Technician 2025/Cp/082
Universidade da Coruña · Murcia, ES
Big Data Office
Organisation/Company: University of A CoruñaResearch Field: Engineering > Computer EngineeringResearcher Profile: First Stage Researcher (R1)Positions: Bachelor PositionsCountry: SpainApplication Deadline: 21 May 2025 - 15:00 (Europe/Brussels)Type of Contract: PermanentJob Status: Part-timeHours Per Week: 17.5Offer Starting Date: 1 Sep 2025Funding: Not funded by an EU programmeReference Number: 2025/CP/082Research Title: AXUDAS PARA A CONSOLIDACIÓN E ESTRUTURACIÓN DE UNIDADES DE INVESTIGACIÓN COMPETITIVAS.
GPCOffer DescriptionGrant/funding reference: ED431B 2024/21Research line: Computer Science and Information TechnologyLocation & Schedule: CITIC - Monday to Friday: 10:30 - 14:00hTasks to PerformDevelopment of tools for validation of unsupervised classification of astronomical objects observed by Gaia within the DPAC consortium and CU8 unit.Validation of star parameterization results using Gaia RVS data, including external validation with astronomical sources and internal validation considering observational and neural network errors, as well as quantification of confidence intervals and studies of objects with anomalous chemical abundances.Development of deep learning techniques for reducing data dimensionality to enhance star parameterization.Development of generative deep learning methods for classifying non-parameterized sources and improving existing star data.Estimation of errors in distances derived from parallaxes using Bayesian statistics.Support in generating documentation for the project.Minimum Requirements1.
Academic record: Degree in computer engineering (1 point), master's related to the field (1 point).2.
Knowledge of English: B2=0.25 points; C1=0.5 points; C2=1 point.3.
Relevant work/research experience: including scholarships, research projects, publications, contracts, patents, and software registrations.4.
Experience with Gaia data analysis, especially spectra processing and high-resolution stellar spectra analysis.5.
Internationalization activities: participation in scientific meetings, research stays, training schools, dissemination activities.6.
Specific experience in AI, deep learning, classification, and clustering in Big Data Astronomy.Note: The position may be vacated if no candidate scores above 6 points.Selection ProcessApply via UDC online services, addressing applications to the Office of the Vice-Rectorate for Research and Transference, including the call reference.
Deadline: 5 working days after publication.Additional RequirementsDocuments needed: ID, degree certificate, CV, declarations of eligibility and data veracity.
For international candidates, contact ****** for instructions.
#J-18808-Ljbffr
Universidade da Coruña
Eivissa, ES
Research Support Technician 2025/Cp/082
Universidade da Coruña · Eivissa, ES
Big Data Office
Organisation/Company: University of A CoruñaResearch Field: Engineering > Computer EngineeringResearcher Profile: First Stage Researcher (R1)Positions: Bachelor PositionsCountry: SpainApplication Deadline: 21 May 2025 - 15:00 (Europe/Brussels)Type of Contract: PermanentJob Status: Part-timeHours Per Week: 17.5Offer Starting Date: 1 Sep 2025Funding: Not funded by an EU programmeReference Number: 2025/CP/082Research Title: AXUDAS PARA A CONSOLIDACIÓN E ESTRUTURACIÓN DE UNIDADES DE INVESTIGACIÓN COMPETITIVAS.
GPCOffer DescriptionGrant/funding reference: ED431B 2024/21Research line: Computer Science and Information TechnologyLocation & Schedule: CITIC - Monday to Friday: 10:30 - 14:00hTasks to PerformDevelopment of tools for validation of unsupervised classification of astronomical objects observed by Gaia within the DPAC consortium and CU8 unit.Validation of star parameterization results using Gaia RVS data, including external validation with astronomical sources and internal validation considering observational and neural network errors, as well as quantification of confidence intervals and studies of objects with anomalous chemical abundances.Development of deep learning techniques for reducing data dimensionality to enhance star parameterization.Development of generative deep learning methods for classifying non-parameterized sources and improving existing star data.Estimation of errors in distances derived from parallaxes using Bayesian statistics.Support in generating documentation for the project.Minimum Requirements1.
Academic record: Degree in computer engineering (1 point), master's related to the field (1 point).2.
Knowledge of English: B2=0.25 points; C1=0.5 points; C2=1 point.3.
Relevant work/research experience: including scholarships, research projects, publications, contracts, patents, and software registrations.4.
Experience with Gaia data analysis, especially spectra processing and high-resolution stellar spectra analysis.5.
Internationalization activities: participation in scientific meetings, research stays, training schools, dissemination activities.6.
Specific experience in AI, deep learning, classification, and clustering in Big Data Astronomy.Note: The position may be vacated if no candidate scores above 6 points.Selection ProcessApply via UDC online services, addressing applications to the Office of the Vice-Rectorate for Research and Transference, including the call reference.
Deadline: 5 working days after publication.Additional RequirementsDocuments needed: ID, degree certificate, CV, declarations of eligibility and data veracity.
For international candidates, contact ****** for instructions.
#J-18808-Ljbffr
Universidade da Coruña
Almería, ES
Research Support Technician 2025/Cp/082
Universidade da Coruña · Almería, ES
Big Data Office
Organisation/Company: University of A CoruñaResearch Field: Engineering > Computer EngineeringResearcher Profile: First Stage Researcher (R1)Positions: Bachelor PositionsCountry: SpainApplication Deadline: 21 May 2025 - 15:00 (Europe/Brussels)Type of Contract: PermanentJob Status: Part-timeHours Per Week: 17.5Offer Starting Date: 1 Sep 2025Funding: Not funded by an EU programmeReference Number: 2025/CP/082Research Title: AXUDAS PARA A CONSOLIDACIÓN E ESTRUTURACIÓN DE UNIDADES DE INVESTIGACIÓN COMPETITIVAS.
GPCOffer DescriptionGrant/funding reference: ED431B 2024/21Research line: Computer Science and Information TechnologyLocation & Schedule: CITIC - Monday to Friday: 10:30 - 14:00hTasks to PerformDevelopment of tools for validation of unsupervised classification of astronomical objects observed by Gaia within the DPAC consortium and CU8 unit.Validation of star parameterization results using Gaia RVS data, including external validation with astronomical sources and internal validation considering observational and neural network errors, as well as quantification of confidence intervals and studies of objects with anomalous chemical abundances.Development of deep learning techniques for reducing data dimensionality to enhance star parameterization.Development of generative deep learning methods for classifying non-parameterized sources and improving existing star data.Estimation of errors in distances derived from parallaxes using Bayesian statistics.Support in generating documentation for the project.Minimum Requirements1.
Academic record: Degree in computer engineering (1 point), master's related to the field (1 point).2.
Knowledge of English: B2=0.25 points; C1=0.5 points; C2=1 point.3.
Relevant work/research experience: including scholarships, research projects, publications, contracts, patents, and software registrations.4.
Experience with Gaia data analysis, especially spectra processing and high-resolution stellar spectra analysis.5.
Internationalization activities: participation in scientific meetings, research stays, training schools, dissemination activities.6.
Specific experience in AI, deep learning, classification, and clustering in Big Data Astronomy.Note: The position may be vacated if no candidate scores above 6 points.Selection ProcessApply via UDC online services, addressing applications to the Office of the Vice-Rectorate for Research and Transference, including the call reference.
Deadline: 5 working days after publication.Additional RequirementsDocuments needed: ID, degree certificate, CV, declarations of eligibility and data veracity.
For international candidates, contact ****** for instructions.
#J-18808-Ljbffr
Universidade da Coruña
Santiago de Compostela, ES
Research Support Technician 2025/Cp/082
Universidade da Coruña · Santiago de Compostela, ES
Big Data Office
Organisation/Company: University of A CoruñaResearch Field: Engineering > Computer EngineeringResearcher Profile: First Stage Researcher (R1)Positions: Bachelor PositionsCountry: SpainApplication Deadline: 21 May 2025 - 15:00 (Europe/Brussels)Type of Contract: PermanentJob Status: Part-timeHours Per Week: 17.5Offer Starting Date: 1 Sep 2025Funding: Not funded by an EU programmeReference Number: 2025/CP/082Research Title: AXUDAS PARA A CONSOLIDACIÓN E ESTRUTURACIÓN DE UNIDADES DE INVESTIGACIÓN COMPETITIVAS.
GPCOffer DescriptionGrant/funding reference: ED431B 2024/21Research line: Computer Science and Information TechnologyLocation & Schedule: CITIC - Monday to Friday: 10:30 - 14:00hTasks to PerformDevelopment of tools for validation of unsupervised classification of astronomical objects observed by Gaia within the DPAC consortium and CU8 unit.Validation of star parameterization results using Gaia RVS data, including external validation with astronomical sources and internal validation considering observational and neural network errors, as well as quantification of confidence intervals and studies of objects with anomalous chemical abundances.Development of deep learning techniques for reducing data dimensionality to enhance star parameterization.Development of generative deep learning methods for classifying non-parameterized sources and improving existing star data.Estimation of errors in distances derived from parallaxes using Bayesian statistics.Support in generating documentation for the project.Minimum Requirements1.
Academic record: Degree in computer engineering (1 point), master's related to the field (1 point).2.
Knowledge of English: B2=0.25 points; C1=0.5 points; C2=1 point.3.
Relevant work/research experience: including scholarships, research projects, publications, contracts, patents, and software registrations.4.
Experience with Gaia data analysis, especially spectra processing and high-resolution stellar spectra analysis.5.
Internationalization activities: participation in scientific meetings, research stays, training schools, dissemination activities.6.
Specific experience in AI, deep learning, classification, and clustering in Big Data Astronomy.Note: The position may be vacated if no candidate scores above 6 points.Selection ProcessApply via UDC online services, addressing applications to the Office of the Vice-Rectorate for Research and Transference, including the call reference.
Deadline: 5 working days after publication.Additional RequirementsDocuments needed: ID, degree certificate, CV, declarations of eligibility and data veracity.
For international candidates, contact ****** for instructions.
#J-18808-Ljbffr
Universidade da Coruña
Coruña, A, ES
Research Support Technician 2025/Cp/082
Universidade da Coruña · Coruña, A, ES
Big Data Office
Organisation/Company: University of A CoruñaResearch Field: Engineering > Computer EngineeringResearcher Profile: First Stage Researcher (R1)Positions: Bachelor PositionsCountry: SpainApplication Deadline: 21 May 2025 - 15:00 (Europe/Brussels)Type of Contract: PermanentJob Status: Part-timeHours Per Week: 17.5Offer Starting Date: 1 Sep 2025Funding: Not funded by an EU programmeReference Number: 2025/CP/082Research Title: AXUDAS PARA A CONSOLIDACIÓN E ESTRUTURACIÓN DE UNIDADES DE INVESTIGACIÓN COMPETITIVAS.
GPCOffer DescriptionGrant/funding reference: ED431B 2024/21Research line: Computer Science and Information TechnologyLocation & Schedule: CITIC - Monday to Friday: 10:30 - 14:00hTasks to PerformDevelopment of tools for validation of unsupervised classification of astronomical objects observed by Gaia within the DPAC consortium and CU8 unit.Validation of star parameterization results using Gaia RVS data, including external validation with astronomical sources and internal validation considering observational and neural network errors, as well as quantification of confidence intervals and studies of objects with anomalous chemical abundances.Development of deep learning techniques for reducing data dimensionality to enhance star parameterization.Development of generative deep learning methods for classifying non-parameterized sources and improving existing star data.Estimation of errors in distances derived from parallaxes using Bayesian statistics.Support in generating documentation for the project.Minimum Requirements1.
Academic record: Degree in computer engineering (1 point), master's related to the field (1 point).2.
Knowledge of English: B2=0.25 points; C1=0.5 points; C2=1 point.3.
Relevant work/research experience: including scholarships, research projects, publications, contracts, patents, and software registrations.4.
Experience with Gaia data analysis, especially spectra processing and high-resolution stellar spectra analysis.5.
Internationalization activities: participation in scientific meetings, research stays, training schools, dissemination activities.6.
Specific experience in AI, deep learning, classification, and clustering in Big Data Astronomy.Note: The position may be vacated if no candidate scores above 6 points.Selection ProcessApply via UDC online services, addressing applications to the Office of the Vice-Rectorate for Research and Transference, including the call reference.
Deadline: 5 working days after publication.Additional RequirementsDocuments needed: ID, degree certificate, CV, declarations of eligibility and data veracity.
For international candidates, contact ****** for instructions.
#J-18808-Ljbffr
Universidade da Coruña
Marbella, ES
Research Support Technician 2025/Cp/082
Universidade da Coruña · Marbella, ES
Big Data Office
Organisation/Company: University of A CoruñaResearch Field: Engineering > Computer EngineeringResearcher Profile: First Stage Researcher (R1)Positions: Bachelor PositionsCountry: SpainApplication Deadline: 21 May 2025 - 15:00 (Europe/Brussels)Type of Contract: PermanentJob Status: Part-timeHours Per Week: 17.5Offer Starting Date: 1 Sep 2025Funding: Not funded by an EU programmeReference Number: 2025/CP/082Research Title: AXUDAS PARA A CONSOLIDACIÓN E ESTRUTURACIÓN DE UNIDADES DE INVESTIGACIÓN COMPETITIVAS.
GPCOffer DescriptionGrant/funding reference: ED431B 2024/21Research line: Computer Science and Information TechnologyLocation & Schedule: CITIC - Monday to Friday: 10:30 - 14:00hTasks to PerformDevelopment of tools for validation of unsupervised classification of astronomical objects observed by Gaia within the DPAC consortium and CU8 unit.Validation of star parameterization results using Gaia RVS data, including external validation with astronomical sources and internal validation considering observational and neural network errors, as well as quantification of confidence intervals and studies of objects with anomalous chemical abundances.Development of deep learning techniques for reducing data dimensionality to enhance star parameterization.Development of generative deep learning methods for classifying non-parameterized sources and improving existing star data.Estimation of errors in distances derived from parallaxes using Bayesian statistics.Support in generating documentation for the project.Minimum Requirements1.
Academic record: Degree in computer engineering (1 point), master's related to the field (1 point).2.
Knowledge of English: B2=0.25 points; C1=0.5 points; C2=1 point.3.
Relevant work/research experience: including scholarships, research projects, publications, contracts, patents, and software registrations.4.
Experience with Gaia data analysis, especially spectra processing and high-resolution stellar spectra analysis.5.
Internationalization activities: participation in scientific meetings, research stays, training schools, dissemination activities.6.
Specific experience in AI, deep learning, classification, and clustering in Big Data Astronomy.Note: The position may be vacated if no candidate scores above 6 points.Selection ProcessApply via UDC online services, addressing applications to the Office of the Vice-Rectorate for Research and Transference, including the call reference.
Deadline: 5 working days after publication.Additional RequirementsDocuments needed: ID, degree certificate, CV, declarations of eligibility and data veracity.
For international candidates, contact ****** for instructions.
#J-18808-Ljbffr
Universidade da Coruña
Oviedo, ES
Research Support Technician 2025/Cp/082
Universidade da Coruña · Oviedo, ES
Big Data Office
Organisation/Company: University of A CoruñaResearch Field: Engineering > Computer EngineeringResearcher Profile: First Stage Researcher (R1)Positions: Bachelor PositionsCountry: SpainApplication Deadline: 21 May 2025 - 15:00 (Europe/Brussels)Type of Contract: PermanentJob Status: Part-timeHours Per Week: 17.5Offer Starting Date: 1 Sep 2025Funding: Not funded by an EU programmeReference Number: 2025/CP/082Research Title: AXUDAS PARA A CONSOLIDACIÓN E ESTRUTURACIÓN DE UNIDADES DE INVESTIGACIÓN COMPETITIVAS.
GPCOffer DescriptionGrant/funding reference: ED431B 2024/21Research line: Computer Science and Information TechnologyLocation & Schedule: CITIC - Monday to Friday: 10:30 - 14:00hTasks to PerformDevelopment of tools for validation of unsupervised classification of astronomical objects observed by Gaia within the DPAC consortium and CU8 unit.Validation of star parameterization results using Gaia RVS data, including external validation with astronomical sources and internal validation considering observational and neural network errors, as well as quantification of confidence intervals and studies of objects with anomalous chemical abundances.Development of deep learning techniques for reducing data dimensionality to enhance star parameterization.Development of generative deep learning methods for classifying non-parameterized sources and improving existing star data.Estimation of errors in distances derived from parallaxes using Bayesian statistics.Support in generating documentation for the project.Minimum Requirements1.
Academic record: Degree in computer engineering (1 point), master's related to the field (1 point).2.
Knowledge of English: B2=0.25 points; C1=0.5 points; C2=1 point.3.
Relevant work/research experience: including scholarships, research projects, publications, contracts, patents, and software registrations.4.
Experience with Gaia data analysis, especially spectra processing and high-resolution stellar spectra analysis.5.
Internationalization activities: participation in scientific meetings, research stays, training schools, dissemination activities.6.
Specific experience in AI, deep learning, classification, and clustering in Big Data Astronomy.Note: The position may be vacated if no candidate scores above 6 points.Selection ProcessApply via UDC online services, addressing applications to the Office of the Vice-Rectorate for Research and Transference, including the call reference.
Deadline: 5 working days after publication.Additional RequirementsDocuments needed: ID, degree certificate, CV, declarations of eligibility and data veracity.
For international candidates, contact ****** for instructions.
#J-18808-Ljbffr
Universidade da Coruña
Gijón, ES
Research Support Technician 2025/Cp/082
Universidade da Coruña · Gijón, ES
Big Data Office
Organisation/Company: University of A CoruñaResearch Field: Engineering > Computer EngineeringResearcher Profile: First Stage Researcher (R1)Positions: Bachelor PositionsCountry: SpainApplication Deadline: 21 May 2025 - 15:00 (Europe/Brussels)Type of Contract: PermanentJob Status: Part-timeHours Per Week: 17.5Offer Starting Date: 1 Sep 2025Funding: Not funded by an EU programmeReference Number: 2025/CP/082Research Title: AXUDAS PARA A CONSOLIDACIÓN E ESTRUTURACIÓN DE UNIDADES DE INVESTIGACIÓN COMPETITIVAS.
GPCOffer DescriptionGrant/funding reference: ED431B 2024/21Research line: Computer Science and Information TechnologyLocation & Schedule: CITIC - Monday to Friday: 10:30 - 14:00hTasks to PerformDevelopment of tools for validation of unsupervised classification of astronomical objects observed by Gaia within the DPAC consortium and CU8 unit.Validation of star parameterization results using Gaia RVS data, including external validation with astronomical sources and internal validation considering observational and neural network errors, as well as quantification of confidence intervals and studies of objects with anomalous chemical abundances.Development of deep learning techniques for reducing data dimensionality to enhance star parameterization.Development of generative deep learning methods for classifying non-parameterized sources and improving existing star data.Estimation of errors in distances derived from parallaxes using Bayesian statistics.Support in generating documentation for the project.Minimum Requirements1.
Academic record: Degree in computer engineering (1 point), master's related to the field (1 point).2.
Knowledge of English: B2=0.25 points; C1=0.5 points; C2=1 point.3.
Relevant work/research experience: including scholarships, research projects, publications, contracts, patents, and software registrations.4.
Experience with Gaia data analysis, especially spectra processing and high-resolution stellar spectra analysis.5.
Internationalization activities: participation in scientific meetings, research stays, training schools, dissemination activities.6.
Specific experience in AI, deep learning, classification, and clustering in Big Data Astronomy.Note: The position may be vacated if no candidate scores above 6 points.Selection ProcessApply via UDC online services, addressing applications to the Office of the Vice-Rectorate for Research and Transference, including the call reference.
Deadline: 5 working days after publication.Additional RequirementsDocuments needed: ID, degree certificate, CV, declarations of eligibility and data veracity.
For international candidates, contact ****** for instructions.
#J-18808-Ljbffr
Universidade da Coruña
Logroño, ES
Research Support Technician 2025/Cp/082
Universidade da Coruña · Logroño, ES
Big Data Office
Organisation/Company: University of A CoruñaResearch Field: Engineering > Computer EngineeringResearcher Profile: First Stage Researcher (R1)Positions: Bachelor PositionsCountry: SpainApplication Deadline: 21 May 2025 - 15:00 (Europe/Brussels)Type of Contract: PermanentJob Status: Part-timeHours Per Week: 17.5Offer Starting Date: 1 Sep 2025Funding: Not funded by an EU programmeReference Number: 2025/CP/082Research Title: AXUDAS PARA A CONSOLIDACIÓN E ESTRUTURACIÓN DE UNIDADES DE INVESTIGACIÓN COMPETITIVAS.
GPCOffer DescriptionGrant/funding reference: ED431B 2024/21Research line: Computer Science and Information TechnologyLocation & Schedule: CITIC - Monday to Friday: 10:30 - 14:00hTasks to PerformDevelopment of tools for validation of unsupervised classification of astronomical objects observed by Gaia within the DPAC consortium and CU8 unit.Validation of star parameterization results using Gaia RVS data, including external validation with astronomical sources and internal validation considering observational and neural network errors, as well as quantification of confidence intervals and studies of objects with anomalous chemical abundances.Development of deep learning techniques for reducing data dimensionality to enhance star parameterization.Development of generative deep learning methods for classifying non-parameterized sources and improving existing star data.Estimation of errors in distances derived from parallaxes using Bayesian statistics.Support in generating documentation for the project.Minimum Requirements1.
Academic record: Degree in computer engineering (1 point), master's related to the field (1 point).2.
Knowledge of English: B2=0.25 points; C1=0.5 points; C2=1 point.3.
Relevant work/research experience: including scholarships, research projects, publications, contracts, patents, and software registrations.4.
Experience with Gaia data analysis, especially spectra processing and high-resolution stellar spectra analysis.5.
Internationalization activities: participation in scientific meetings, research stays, training schools, dissemination activities.6.
Specific experience in AI, deep learning, classification, and clustering in Big Data Astronomy.Note: The position may be vacated if no candidate scores above 6 points.Selection ProcessApply via UDC online services, addressing applications to the Office of the Vice-Rectorate for Research and Transference, including the call reference.
Deadline: 5 working days after publication.Additional RequirementsDocuments needed: ID, degree certificate, CV, declarations of eligibility and data veracity.
For international candidates, contact ****** for instructions.
#J-18808-Ljbffr
