Post-doctoral research fellowship: ARDITI-CLIMAREST-2023-001
A call is open for 1 (one) researcher at ARDITI (Funchal, Portugal), under the Project CLIMAREST - Coastal Climate Resilience and Marine Restoration Tools for the Arctic Atlantic basin (GA 101093865), under the following conditions:
Reference ARDITI-CLIMAREST-2023-001; Scientific area: Data Science Sub-research field: Computer Science |
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Project Summary:The project CLIMAREST: Coastal Climate Resilience and Marine Restoration Tools for the Arctic Atlantic Basin integrates multiple expertise into a holistic approach that aims to develop a flexible overarching toolbox designed to establish guidelines for ecosystem restoration and to enhance climate resilience in coastal communities. The concept is to develop, test, and optimise a modular toolbox that integrates expert knowledge, scientific information, multilevel stakeholder and community involvement, ecosystem service improvement analysis, cost-benefit analysis, priority of actions, and custom-designed protocols for restoring and monitoring multiple coastal habitats. The toolbox framework will have common and specific tools that will be tested, optimised, and demonstrated in five different ecosystems across a latitudinal gradient of the Arctic-Atlantic basin, ranging from the high-Arctic Svalbard (79° N) in the north to the Madeira archipelago (33° N) in the south. In Madeira, project CLIMAREST will leverage opportunistic datasets from the existing mobile applications and digital platform tools for web-based surveys, allowing the reach out to a wide stakeholder audience, enabling citizen and stakeholder participation in monitoring restoration activities and scenarios. Within the scope of this project, ARDITI (Agência Regional para o Desenvolvimento da Investigação, Tecnologia e Inovação) is seeking to recruit a Post-doctoral research fellow with a Ph.D. degree in Computer Science, Data Science or another field of relevance awarded within the last 36 months, with previous expertise in data science. Prospective candidates are expected to: assist in the framework design for data infrastructure, including mobile applications and online survey tools, data collection procedures and efforts, data management strategy, and in data analysis from multiple data sources, including biological and ecological data, questionnaire survey data, imagery data, and socio-economic data. The position requires prior experience with statistics, Python programming, website frontend, and backend design and development, database management and maintenance, data compilation, analysis and reporting, and structuring and writing technical reports and peer review manuscripts. Prior familiarity with advanced statistics, including supervised and unsupervised methods for AI training, and AI applications for data science and management (e.g., deep learning, convolutional neural networks), will be valued. The ideal candidate will also be familiar with ecological and biological data and/or ecosystem services valuation. The successful candidate is expected to join MARE - Marine and Environmental Sciences Centre R&D Unit in Madeira (MARE-Madeira) in March 2023. MARE-Madeira researchers conduct their work and projects at different facilities, providing multiple assets for marine-related research, including marine technology and AI, mesocosms, laboratories, and a broad range of field and laboratory equipment. MARE-Madeira currently has several ongoing projects focusing on a wide variety of research fields, such as coastal ecology, marine biological invasion processes, habitat mapping, marine litter, marine mammal ecology and conservation, fisheries, climate change, and human-related stressors and impacts on coastal ecosystems. The main goal will be to contribute to research and studies within the framework of CLIMAREST project, namely in data collection and management strategies, in data integration and analysis, in developing digital tools for data towards assessing the public’s perception of their importance and evaluating economic value and impact of restoration efforts.
Admission RequirementsThe ideal candidate will have a valid Ph.D. Degree (obtained within 36 months prior to the application deadline) in Computer Science, equivalent, or another field of relevance to the CLIMAREST project. The candidates are expected to have previous experience in (but not exclusively):
If a foreign higher education institution awarded the degree, that degree must comply with the provisions of Decreto-Lei no. 66/2018 of 16th August (approves the legal regime for the recognition of foreign higher academic degrees) and Portaria no. 33/2019 of 25th January, and all formalities established therein must be complied with up to the date of hire.
WorkplanThe selected fellow will contribute to the scientific data analysis in Madeira as well as in replication sights. The fellow will participate within the CLIMAREST consortium and be part of internal reporting groups. In addition, the fellow is expected to contribute and assist with project management, data management, and preparing manuscripts and reports. Specifically, the fellows’ work plan will include (but not exclusively) the following:
|
Description |
Max. Score (points) |
Experience with supervised/unsupervised machine learning and algorithms, probabilistic modeling, infrastructure, and multivariate statistics, and/or in its application; |
3 |
Experience in Data Analytics, development of new models and methods in data science; |
3 |
Experience with Python programming language |
3 |
Experience with ML packages (e.g., Scikit Learn, TensorFlow, PyTorch) |
3 |
Experience with Python scientific packages (e.g., NumPy, SciPy, Pandas) |
2 |
Experience with Anaconda (e.g., JupyterLab, Notebook, Spyder) |
2 |
Experience with statistical data visualization tools (e.g., Matplotlib, Seaborn) |
2 |
Some experience in backend and front-end web development (e.g., PHP, Laravel, React.js, HTML, JS, CSS, MySql) |
2 |
Experience Familiarity with ecological data analysis and modeling and/or ecosystem services valuation. |
2 |
Demonstrated ability to work independently; |
1 |
Fluent knowledge (spoken and written) of the English language; |
1 |
Strong communication and collaboration skills. |
1 |
Total |
25 |
IN – Interview
- The top three candidates may be invited for an interview (in person or remotely) if QA + EP scoring has a maximum difference of 2 points or lower. Maximum score of 10 points.
Selection panel
Dr. Marko Radeta (MARE-Madeira, University of Madeira)
Dr. João Canning-Clode (MARE-Madeira, ARDITI)
Dr. João Gama Monteiro (MARE-Madeira, University of Madeira)
Application contents
- Motivation Letter (emphasizing the candidate’s adequacy to each evaluation criteria)
- Curriculum Vitae
- Ph.D. Degree certificate
Announcement of the results
All candidates will be notified by email.
Application submission and deadline
Applications should be submitted in English by email to the following address:
Deadline for application:
12/02/2023 (Lisbon/Madeira Island Time).
Notes:
The selection process will be based on the principle of non-discrimination in respect of gender, age, nationality, religion, racial group, or any other possible discriminatory issue. Selection will be made only based on merit and following the European Charter for Researchers, the Code of Conduct for the Recruitment of Researchers (Commission Recommendation, Brussels, 11.3.2005, 2005/251/EC), and the recommendations from the San Francisco Declaration on Research Assessment (DORA).
ARDITI is a recognized “refugee welcoming organization" by the European Commission, follows the European Charter for Researchers, and welcomes applications from all qualified individuals.
Vacant posts: 1
Organization contact data:
ARDITI - Agência Regional para o Desenvolvimento da Investigação, Tecnologia e Inovação
Edif. Madeira Tecnopolo, Piso 2
Caminho da Penteada
9020-105 Funchal
Portugal
tel. +351 291 721 220
email:
Número de vagas: 1
Tipo de contrato: Bolsa de Investigação Pós-Doutoral
País: Portugal
Localidade: Funchal
Instituição de acolhimento: ARDITI
Data limite de candidatura: 12 de fevereiro de 2023
(A data limite de candidatura deve ser confirmada no texto do anúncio)