PhD Researcher

Research Field: Environmental science » Other Researcher Profile: First Stage Researcher (R1) Positions: PhD Positions Application Deadline: 28 Sep 2026 - 23:59 (Europe/Lisbon) Country: Portugal Type of Contract: Other Type of Contract Extra Information: Unfixed term employment contract Job Status: Full-time Hours Per Week: 35 Offer Starting Date: 15 Sep 2026 Is the job funded through the EU Research Framework Programme?: Not funded by a EU programme Is the Job related to staff position within a Research Infrastructure?: No Offer Description By decision of the Board of Directors, NOVA.id.FCT - Associação para a Inovação e Desenvolvimento da FCT (“NOVA.id.FCT”) opens an international call to hire a PhD Researcher, with the internal reference “#NOVAID295”, under a unfixed term employment contract to conduct research activities in the field of Computation Applied to Environmental Sciences and Engineering and Sustainability, in the scope of the R & D Unit “Centro de Investigação em Ambiente e Sustentabilidade” (CENSE) (UID/4085/2025), financed by Fundação para a Ciência e a Tecnologia, I.P./MCTES (FCT, I.P.) through national funds (PIDDAC) (OE). Type of contract and applicable legislation The hiring of the PhD Researcher shall be made by means of an Unfixed Term Employment Contract entered into in accordance with the Portuguese Labour Code approved by the Law no. 7/2009 of February 12th, as amended. The contract should have a forecasted duration of 12 months and should not be extended further than the project duration (maximum 36 months). The contract should begin on October, 2026. The present hiring procedure is further governed inter alia by Decree-law no. 57/2016 of August 29th, as amended by the Law no. 57/2017 of July 19th and Regulatory decree no. 11-A/2017 of December 29th. Main attributions and activities and exclusivity The PhD Researcher shall: Support CENSE’s research activities by enhancing research capabilities in the field of data analysis and artificial intelligence as applied to ongoing projects in the area of the environment and sustainability; Investigate and apply artificial intelligence and machine learning techniques, including large language models (LLMs), across CENSE’s scientific body in its five thematic areas; Build data and knowledge infrastructures, namely knowledge graphs, ontologies and multimodal representations of the CENSE scientific body; Collaborate with the CENSE team and external partners in the design, execution and dissemination of research projects funded by competitive national and international grants in the field. The PhD Researcher shall fully devote the whole of his/her professional activity to NOVA.id.FCT, on an exclusive basis, unless it opts for the full-time regime, as stated in article 7.º, number 1 of Decree-Law n.º 57/2016, of August 29th, altered by Law n.º 57/2017, of July 19th. Place of work The PhD Researcher’s working place shall be at the premises of Department of Environmental Sciences and Engineering located in Faculdade de Ciências e Tecnologia da Universidade Nova de Lisboa (NOVA FCT) - Campus da Caparica and he/she shall travel, in Portugal or abroad, as required by his/her attributions or as necessary for his/her activity. Monthly remuneration The PhD Researcher shall earn a monthly remuneration in the gross amount of €2.408,11, pursuant to number 2 of Article 15 of Decree-Law no. 57/2016 of August 29th, as amended by Law no. 57/2017 of July 19th, and Regulatory Decree no. 11-A / 2017, of December 29, corrected through the amendment produced by Decree-Law no. 10-B / 2020, of 20 March. The monthly remuneration will be two thirds of the abovementioned if the investigator opts for the full-time regime. Admission Requirements Applicants to this call may be national, foreign or stateless candidates holding a PhD degree in the field of Environmental Science and/or Engineering, Environment and Sustainability, Chemistry, Computer Science, Data Science, Applied Mathematics or related fields, legally valid and/or recognized in Portugal and complying with the following specific requirements: a) Experience in the application of data analysis and machine learning methods to scientific data (e.g. multivariate analysis, chemometrics, neural networks, classification or regression models); familiarity with large language models (LLMs) and other artificial intelligence techniques is valued; b) Experience in the processing, integration and analysis of heterogeneous scientific data (e.g. instrumental, laboratory, environmental, numerical and categorical data, text, geospatial data or time series); c) Experience in Python programming and in data analysis and machine learning libraries (Scikit-learn, pandas, NumPy or similar); experience with AI/ML frameworks (PyTorch, HuggingFace, LangChain or similar) and the development of publicly available scientific software is valued; d) Ability to work in a multidisciplinary team and in a collaborative research context with external partners; e) Communication skills (oral and written) in Portuguese and English. Evaluation of the Applications and Composition of the Jury Applications shall be subject to evaluation by a jury that shall follow the procedure established in articles 13 and 14 (by virtue of article 19) of Decree-Law no. 57/2016 of August 29th, as amended by Law no. 57/2017 of July 19th. Pursuant to Article 13 of Decree-Law no. 57/2016 the jury is composed of the following members: President: Francisco Manuel Freire Cardoso Ferreira, Professor Associado com Agregação da NOVA FCT Member: Fernando Miguel Pais da Graça Lobo, Professor Associado com Agregação da Universidade do Algarve Member: Laurent Georges Denis Drouet, Professor Auxiliar da NOVA FCT Substitute Member: João Pedro Costa Luz Baptista Gouveia, Investigador Principal da NOVA FCT Substitute Member: Nuno Miguel Ribeiro Videira Costa, Professor Associado da NOVA FCT Selection criteria The selection of the successful candidate will be carried out through the evaluation of the scientific and curricular achievements as established by Decree-Law no. 57/2016 of August 29th, as amended by Law no. 57/2017 of July 19th and the selection criteria and their respective weighting shall be as follows: a) Quantity and quality of scientific publications in the project's field, including environmental sciences and sustainability and scientific data analysis (30%); b) Demonstrated experience in developing computational tools, data pipelines and/or AI systems applied to scientific or environmental data, assessed on the basis of the CV and portfolio, including publicly available software (35%); c) Advanced training and research experience relevant to the project's field, namely in the integration of analytical, environmental and computational data (25%); d) Quality of the interview (10%). All applications will be evaluated on a scale of 0 to 20 points. Only candidates who score 75% or higher in the combined total of criteria (a), (b) and (c) will be invited to the interview and may be offered the position. The interview will be conducted only with the top three candidates based on criteria (a), (b) and (c). Final Decision The final deliberation of the jury shall be homologated by the ultimate governing body of NOVA.id.FCT that is also responsible for the decision of hiring. The list of admitted and excluded candidates and the final list of classification will be publicised on the website of NOVA.id.FCT (www.novaidfct.pt) and sent by electronic mail with receipt of delivery to all candidates. Submission of Applications Applications must be submitted between 15th to 28th September, 2026 by email, addressed to ff@fct.unl.pt and containing a single PDF file with the following documents in Portuguese or English languages: a) Complete CV; b) Motivation letter; c) Doctoral Certificate. Non-discrimination and equal access policy NOVA.id.FCT actively promotes a non-discrimination and equal access policy, reason for which no candidate can be benefited, prejudiced or deprived of any duty, namely age, sex, disability, sexual orientation, chronic illness, nationality, ethnic origin or race, religion or political beliefs. Where to apply E-mail: ff@fct.unl.pt Requirements Research Field: Environmental science » Other Education Level: PhD or equivalent Skills/Qualifications Applicants to this call may be national, foreign or stateless candidates holding a PhD degree in the field of Environmental Science and/or Engineering, Environment and Sustainability, Chemistry, Computer Science, Data Science, Applied Mathematics or related fields, legally valid and/or recognized in Portugal and complying with the following specific requirements: a) Experience in the application of data analysis and machine learning methods to scientific data (e.g. multivariate analysis, chemometrics, neural networks, classification or regression models); familiarity with large language models (LLMs) and other artificial intelligence techniques is valued; b) Experience in the processing, integration and analysis of heterogeneous scientific data (e.g. instrumental, laboratory, environmental, numerical and categorical data, text, geospatial data or time series); c) Experience in Python programming and in data analysis and machine learning libraries (Scikit-learn, pandas, NumPy or similar); experience with AI/ML frameworks (PyTorch, HuggingFace, LangChain or similar) and the development of publicly available scientific software is valued; d) Ability to work in a multidisciplinary team and in a collaborative research context with external partners; e) Communication skills (oral and written) in Portuguese and English. Languages: ENGLISH Level: Excellent Additional Information Benefits The PhD Researcher shall earn a monthly remuneration in the gross amount of €2.408,11, pursuant to number 2 of Article 15 of Decree-Law no. 57/2016 of August 29th, as amended by Law no. 57/2017 of July 19th, and Regulatory Decree no. 11-A / 2017, of December 29, corrected through the amendment produced by Decree-Law no. 10-B / 2020, of 20 March. The monthly remuneration will be two thirds of the abovementioned if the investigator opts for the full-time regime. Eligibility criteria Applicants to this call may be national, foreign or stateless candidates holding a PhD degree in the field of Environmental Science and/or Engineering, Environment and Sustainability, Chemistry, Computer Science, Data Science, Applied Mathematics or related fields, legally valid and/or recognized in Portugal and complying with the following specific requirements: a) Experience in the application of data analysis and machine learning methods to scientific data (e.g. multivariate analysis, chemometrics, neural networks, classification or regression models); familiarity with large language models (LLMs) and other artificial intelligence techniques is valued; b) Experience in the processing, integration and analysis of heterogeneous scientific data (e.g. instrumental, laboratory, environmental, numerical and categorical data, text, geospatial data or time series); c) Experience in Python programming and in data analysis and machine learning libraries (Scikit-learn, pandas, NumPy or similar); experience with AI/ML frameworks (PyTorch, HuggingFace, LangChain or similar) and the development of publicly available scientific software is valued; d) Ability to work in a multidisciplinary team and in a collaborative research context with external partners; e) Communication skills (oral and written) in Portuguese and English. Selection process The selection of the successful candidate will be carried out through the evaluation of the scientific and curricular achievements as established by Decree-Law no. 57/2016 of August 29th, as amended by Law no. 57/2017 of July 19th and the selection criteria and their respective weighting shall be as follows: a) Quantity and quality of scientific publications in the project's field, including environmental sciences and sustainability and scientific data analysis (30%); b) Demonstrated experience in developing computational tools, data pipelines and/or AI systems applied to scientific or environmental data, assessed on the basis of the CV and portfolio, including publicly available software (35%); c) Advanced training and research experience relevant to the project's field, namely in the integration of analytical, environmental and computational data (25%); d) Quality of the interview (10%). All applications will be evaluated on a scale of 0 to 20 points. Only candidates who score 75% or higher in the combined total of criteria (a), (b) and (c) will be invited to the interview and may be offered the position. The interview will be conducted only with the top three candidates based on criteria (a), (b) and (c). Evaluation of the Applications and Composition of the Jury Applications shall be subject to evaluation by a jury that shall follow the procedure established in articles 13 and 14 (by virtue of article 19) of Decree-Law no. 57/2016 of August 29th, as amended by Law no. 57/2017 of July 19th. Pursuant to Article 13 of Decree-Law no. 57/2016 the jury is composed of the following members: President: Francisco Manuel Freire Cardoso Ferreira, Professor Associado com Agregação da NOVA FCT Member: Fernando Miguel Pais da Graça Lobo, Professor Associado com Agregação da Universidade do Algarve Member: Laurent Georges Denis Drouet, Professor Auxiliar da NOVA FCT Substitute Member: João Pedro Costa Luz Baptista Gouveia, Investigador Principal da NOVA FCT Substitute Member: Nuno Miguel Ribeiro Videira Costa, Professor Associado da NOVA FCT Additional comments The final deliberation of the jury shall be homologated by the ultimate governing body of NOVA.id.FCT that is also responsible for the decision of hiring. The list of admitted and excluded candidates and the final list of classification will be publicised on the website of NOVA.id.FCT (www.novaidfct.pt) and sent by electronic mail with receipt of delivery to all candidates. NOVA.id.FCT actively promotes a non-discrimination and equal access policy, reason for which no candidate can be benefited, prejudiced or deprived of any duty, namely age, sex, disability, sexual orientation, chronic illness, nationality, ethnic origin or race, religion or political beliefs. Website for additional job details: https://www.novaidfct.pt/content/NOVAID295.EDI.0.pdf Work Location(s) Number of offers available: 1 Company/Institute: NOVA.id.FCT - Associação para a Inovação e Desenvolvimento da FCT Country: Portugal City: Caparica Postal Code: 2829-516 CAPARICA Street: Campus de Caparica Contact City: Caparica Website: http://www.novaid.fct.unl.pt/ Street: Campus de Caparica Postal Code: 2829-516 Caparica