Universitas Brawijaya, Malang, Indonesia
Universitas Brawijaya, Indonesia, invites applications for a PhD Research Fellow position in machine learning for aquaculture disease forecasting. The position is part of the AQUAROM project, funded by the Research Council of Norway, focusing on resilient aquaculture outbreak management from northern cold to tropical waters. The PhD candidate will be based at the Faculty of Computer Science, Universitas Brawijaya in Malang, Indonesia.
| Work Package | WP3 (Predictive Models) |
| Duration | 3 years |
| Stipend | IDR 6,000,000 - 12,000,000 per month |
| Application Deadline | Open until filled |
| Expected Start Date | As soon as possible |
The PhD candidate will develop machine learning algorithms for disease outbreak forecasting in aquaculture environments characterized by sparse and incomplete data. The research focuses on implementing data augmentation methods (Mixup, SMOTE) and synthetic data generation techniques to handle limited historical data. You will build time-series forecasting models using RNNs, LSTMs, and Transformers, achieving 80%+ accuracy despite sparse sensor coverage.
A key component of the work is developing privacy-preserving machine learning techniques using federated learning and differential privacy for multi-farm data sharing. The research includes applying statistical imputation, interpolation, and anomaly detection methods to handle incomplete and noisy real-world datasets from aquaculture environments. Model validation will be conducted using field trial data from Philippine aquaculture sites, and you will develop decision-support tools with uncertainty quantification for farmers.
The position provides access to high-performance computing resources for AI development. You will collaborate with international partners and are expected to publish at least 3-4 articles in high impact journals.
Applicants must hold a Master's degree in Computer Science, Data Science, Artificial Intelligence, Statistics, or a related field, with a minimum of 2 peer-reviewed publications in machine learning, time-series prediction, deep learning, or data augmentation (at least 1 as first author). Documented research experience in aquaculture, environmental monitoring, or agricultural AI through thesis work or projects is required. A strong machine learning background demonstrated through coursework and projects is essential, along with Python proficiency (NumPy, Pandas, SciPy), ML framework experience (TensorFlow/Keras or PyTorch), and classification and time-series forecasting experience. Experience with sparse, incomplete, and noisy real-world datasets is required, as well as database skills (SQL). English proficiency: TOEFL 550+ or equivalent (IELTS 6.0, TOEFL iBT 79).
Experience with data augmentation techniques (Mixup, SMOTE, synthetic data), deep learning architectures (CNNs, RNNs, LSTMs, Transformers), privacy-preserving ML (federated learning, differential privacy), environmental time-series data (weather, water quality, sensor networks), uncertainty quantification in ML models, and version control systems (Git) are considered advantageous.
The position includes a monthly stipend of IDR 6-12 million based on qualifications, full PhD program support at Universitas Brawijaya with international co-supervision, high-performance computing resources, conference attendance funding (3 annual project workshops plus international AI/ML conferences), research visits to NORCE Norway or Philippines field sites, and access to real-world aquaculture datasets from Norway and Philippines for model training and validation.
Applications must include: cover letter (max 2 pages), CV with complete publication list, academic transcripts (Bachelor's and Master's degree), TOEFL score report, publications (PDFs), research experience documentation (code samples, Jupyter notebooks), three letters of reference (one must be from Master's thesis supervisor), and research proposal (2-3 pages). Please combine all documents into a single PDF file named: AQUAROM_PhD_WP3_[LastName]_[FirstName].pdf
or send application to: hasv@norceresearch.no and moch.ali.fauzi@ub.ac.id
Email subject: PhD AQUAROM WP3 - [Your Full Name]
Dr. Hasan Asyari Arief (Co-Supervisor)
NORCE Research AS
hasv@norceresearch.no
Dr. Muhammad Ali Fauzi (Co-Supervisor)
Faculty of Computer Science, Universitas Brawijaya
moch.ali.fauzi@ub.ac.id