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S2AQUA - Laboratório Colaborativo, Associação para uma Aquacultura Sustentável e Inteligente

Postdoctoral Research Fellowship in Data Modelling for Amy-WARN Project S2AQUA - Collaborative Laboratory, Association for Sustainable and Smart Aquaculture in Portugal

Degree Level

Postdoc

Field of study

Computer Science

Funding

Available

Deadline

Sep 30, 2026

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Country

Portugal

University

S2AQUA - Laboratório Colaborativo, Associação para uma Aquacultura Sustentável e Inteligente

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Keywords

Computer Science
Environmental Science
Biology
Predictive Modeling
Aquaculture
Parasitology
Forecasting
Data-driven Modeling
Bioscience
Statistics
Bioinformatic
ML

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About this position

S2AQUAcoLAB (S2AQUA – Collaborative Laboratory, Association for Sustainable and Smart Aquaculture) is offering a postdoctoral research fellowship in data modelling or related fields within the Amy-WARN project. The project aims to develop a predictive tool to forecast outbreaks caused by A. ocellatum in an operational aquaculture context, combining knowledge of the parasite’s life cycle with environmental monitoring data to identify risk conditions and anticipate outbreaks.

The fellowship is based at the Estação Piloto de Piscicultura de Olhão in Olhão, Portugal, under the supervision of Dr. Sílvia Gregório at S2AQUAcoLAB.

This is a full-time, 12-month fellowship on an exclusive basis, with a monthly maintenance allowance of 1,901.00 EUR. The grant is funded by Algarve 2030, Lisboa 2030, and Orçamento de Estado. The fellow is also entitled to voluntary social insurance reimbursement, where applicable, and personal accident insurance for the duration of the fellowship.

Applicants must hold a PhD in Bioinformatics, Biomedical Sciences, Biology, or another degree that required modelling, obtained within the three years prior to the application date. The profile sought includes experience with machine learning modelling, process-based dynamic models, and programming in a high-level language such as Python or Matlab. Fluency in Portuguese and proficiency in English are required. The notice also highlights teamwork, problem-solving, organisational skills, independence, proactivity, and willingness to work shifts, weekends, and travel when necessary.

Core work includes planning forecasting models, programming models, parameterising them using project data, and contributing to data analysis, reports, scientific articles, and project meetings.

The application window runs from 16 September 2026 to 30 September 2026 at 23:59 (Europe/Lisbon). Applications must be sent by email to [email protected] with the reference S2AQUAcoLAB/Bolsa/Ref_13/2026. Required documents include a detailed signed CV, a short motivation letter, ID/passport copy, proof of qualifications, evidence of professional experience and training, and the required declarations and residence documents where applicable.

Funding details

Available

What's required

Applicants must hold a PhD in Bioinformatics, Biomedical Sciences, Biology, or another degree that required modelling, obtained within the three years prior to the application date. Required experience includes modelling using machine learning techniques and process-based dynamic models, plus programming in a high-level language such as Python or Matlab. Candidates must be fluent in Portuguese and proficient in English (spoken and written). Preferred personal qualities include teamwork, adaptability, problem-solving, strong organisation, responsibility, attention to detail, independence, proactivity, time management, and willingness to work shifts, weekends, and travel domestically and internationally as needed. Applicants must also reside in Portugal permanently and habitually and must not have previously benefited from an FCT-funded research fellowship in companies.

How to apply

Send an email to [email protected] with the reference S2AQUAcoLAB/Bolsa/Ref_13/2026. Include all mandatory documents, especially a signed CV, motivation letter, proof of degree, and required declarations. Applications must be submitted by 2026-09-30 23:59 (Europe/Lisbon).

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