Publisher
source

Daniel Hernández Lobato

Closing soon

5 days ago

PhD in Machine Learning for Human-Aware and Efficient Machine Learning (HEMLA) at Universidad Autónoma de Madrid Universidad Autónoma de Madrid in Spain

Degree Level

PhD

Field of study

Computer Science

Funding

Fully funded four-year FPI PhD position within the HEMLA project. The post mentions access to state-of-the-art computing infrastructure and opportunities for international research stays, collaborations, conferences and workshops.

Deadline

Oct 18, 2026

Country flag

Country

Spain

University

Universidad Autónoma de Madrid

Social connections

How do I apply for this?

Sign in for free to reveal details, requirements, and source links.

Apply for this position

Keywords

Computer Science
Environmental Science
Biomedical Engineering
Deep Learning
Mathematics
Functional Analysis
Python Programming
Uncertainty Analysis
Insurance
Explainable Ai
Optimisation
Kernel Methods
Statistics
ML

Suggested positions

About this position

PhD opportunity in Machine Learning at Universidad Autónoma de Madrid (UAM), within the Human-Aware and Efficient Machine Learning (HEMLA) project and the Machine Learning Group (GAA).

The position is a fully funded four-year FPI PhD focused on developing machine learning methods that are efficient, trustworthy, interpretable, and aligned with human preferences. Research topics include explainable AI, Bayesian deep learning, uncertainty quantification, scalable kernel methods, and functional data analysis, with applications in healthcare and renewable energy forecasting.

Applicants should have a Master's degree or equivalent in a relevant field and a strong background in machine learning, optimisation, probability, or statistics. Programming skills are expected, preferably in Python and PyTorch.

The post highlights access to state-of-the-art computing infrastructure and opportunities for international research stays, collaborations, conferences, and workshops.

To apply, email [email protected] with your CV and academic transcripts before 18 October 2026.

Funding details

Fully funded four-year FPI PhD position within the HEMLA project. The post mentions access to state-of-the-art computing infrastructure and opportunities for international research stays, collaborations, conferences and workshops.

What's required

Applicants should hold a Master's degree or equivalent in a relevant field. A strong background in machine learning, optimisation, probability or statistics is required, and candidates should be comfortable programming, preferably in Python and PyTorch.

How to apply

Email Daniel Hernández Lobato at [email protected] with your CV and academic transcripts before 18 October 2026.

More information can be found here

Ask ApplyKite AI

Start chatting
Can you summarize this position?
What qualifications are required for this position?
How should I prepare my application?

Professors