Post-Doctoral Research Visit F/M Fast generation of approximate galaxy maps with topology-infus[...]

TN France; Provence-Alpes-Côte d'Azur; Sur place; EUR 40 000 - 70 000; Plein temps

Résumé du poste

An established research institution is seeking a Post-Doctoral Researcher to explore innovative integrations of Topological Data Analysis with Deep Generative Models. This role focuses on developing mathematical frameworks and applying cutting-edge techniques to simulate and analyze galaxy maps for cosmology. The ideal candidate will possess a PhD in applied mathematics or computer science, along with strong programming skills and a collaborative spirit. This position offers a unique opportunity to contribute to groundbreaking research while enjoying a supportive work environment with flexible hours and ample leave. If you're passionate about advancing scientific knowledge, this is the perfect role for you.

Prestations

Partial reimbursement of public transport costs

7 weeks annual leave + 10 RTT days

Flexible working hours

Teleworking options

Provision of professional equipment

Participation in social, cultural, and sports activities

Access to vocational training

Mutual insurance contributions

Qualifications

• PhD in applied mathematics or computer science required.
• Strong programming skills and experience with data science libraries.

Responsabilités

• Develop mathematical frameworks for topological data analysis.
• Implement TDA methods and apply them to generate galaxy data.

Connaissances

Python

C++

Data Science Libraries (Scikit-Learn, TensorFlow, PyTorch)

Deep Generative Models

Machine Learning

Dimensionality Reduction

Non-convex Optimization

Topological Data Analysis

Collaboration Skills

Communication Skills

Formation

PhD in Applied Mathematics

PhD in Computer Science

Description du poste

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Post-Doctoral Research Visit F/M Fast generation of approximate galaxy maps with topology-infused generative models, Technopole de Sophia Antipolis

Client:

INRIA

Location:

Inria, Sophia Antipolis, France

Job Category:

Research/Academic

EU work permit required:

Yes

Job Reference:

b33a462d51d5

Job Views:

1

Posted:

29.04.2025

Expiry Date:

13.06.2025

Job Description:

The research will be supervised by Mathieu Carrière (DataShape, Centre Inria d’Université Côte d’Azur), with regular meetings organized with collaborators in Area Science Park, Trieste, Italy. The candidate will be located principally at Inria.

Applicants should hold a PhD in applied mathematics and/or computer science, with strong programming skills and experience in data science libraries such as Scikit-Learn, TensorFlow, and PyTorch. Research experience in deep generative models, machine learning, dimensionality reduction, and non-convex optimization is essential. Knowledge of geometric and topological methods in machine learning and approximate cosmological simulations is a plus. Excellent teamwork, communication, and collaboration skills are required.

Prerequisites

• Academic level: PhD

Research Focus

The position aims to explore the theoretical and practical integration of Topological Data Analysis (TDA) with Deep Generative Models (DGM), especially in the context of simulating galaxy maps for cosmology. The role involves developing mathematical frameworks, implementing TDA methods, and applying these to generate and analyze galaxy data, with a focus on topologically constrained generative models like multimodal variational autoencoders.

Key Topics

• Topological Data Analysis (TDA), persistence diagrams, Mapper complexes
• Differentiability of topological descriptors
• Design of topology-based deep generative models
• Application to cosmological data and galaxy map simulations

Research Outputs

Publications in top data science and machine learning conferences, development of novel models, and contributions to understanding the differentiability and application of TDA in generative modeling.

Technical Skills and Level Required:

Languages: Python, C++ (preferred)

Relational skills: Teamwork, communication, collaboration

Valued Skills: Experience with algebraic topology, topological data analysis, and cosmological simulations

Advantages

• Partial reimbursement of public transport costs
• 7 weeks annual leave + 10 RTT days + exceptional leave options
• Flexible working hours and teleworking options
• Provision of professional equipment
• Participation in social, cultural, and sports activities
• Access to vocational training
• Mutual insurance contributions (conditions apply)