Postdoc on Bayesian Monte Carlo for Photo-Realistic Rendering

tendersglobal.net


24 Jan 2024
Job Information
Organisation/Company
Universitat de Barcelona
Department
Organisation profile
Research Field
Computer science » 3 D modelling
Technology » Graphic techniques
Researcher Profile
Recognised Researcher (R2)
Country
Spain
Application Deadline
7 Feb 2024 – 23:59 (Europe/Madrid)
Type of Contract
Temporary
Job Status
Full-time
Is the job funded through the EU Research Framework Programme?
European Union / Next Generation EU
Reference Number
CNS2022-135480
Is the Job related to staff position within a Research Infrastructure?
No

Offer Description
Project Objectives

Physically-based rendering (PBR) requires an accurate reproduction of the physical behavior of light and its interaction with the surface materials, which is formalized by the rendering equation. The typical approach to solve the illumination integral is by resorting to Classical Monte Carlo (CMC), thanks to its simplicity and ease of implementation. However, CMC requires a large number of samples to obtain an accurate estimate, even when coupled with variance reduction techniques. To address this issue several methods have been proposed in the literature, among which Bayesian Monte Carlo (BMC) and other Gaussian Process-based approaches with promising results. Nevertheless, the use of BMC in CG is still in an incipient phase and its application to more evolved and widely used rendering algorithms remains cumbersome. This research project proposes to investigate and develop efficient solutions to generalize the application of this very promising technique to PBR.

Candidate Qualifications

Candidates must hold a PhD in computer science, physics, mathematics, or in a related discipline, and have a strong publication record in their respective field. A solid mathematical background is required, as well as good programming skills in C++, Python and/or Matlab. Experience in Rendering techniques and/or Machine Learning is highly valued. Experience with Monte Carlo methods is also a plus.

Work Environment

The work will be developed within the context of a Research Consolidation grant (09/2023 to 08/2025) awarded to Dr. Ricardo Marques, and will be carried on within the Department of Mathematics and Informatics of the University of Barcelona, a multidisciplinary and extremely dynamic research environment. The selected candidate will have the opportunity collaborate with a PhD Student on the topic of Bayesian Monte Carlo for Photo-Realistic Rendering currently supervised by Dr. Ricardo Marques at University Pompeu Fabra, as well as to benefit from the national and international research collaborations of Dr. Ricardo Marques. For further inquiries please contact Dr. Ricardo Marques ([email protected] ).

Requirements

Research Field
Computer science
Education Level
PhD or equivalent

Skills/Qualifications

Candidates must hold a PhD in computer science, physics, mathematics, or in a related discipline, and have a strong publication record in their respective field. A solid mathematical background is required, as well as good programming skills in C++, Python and/or Matlab. Experience in Rendering techniques and/or Machine Learning is highly valued. Experience with Monte Carlo methods is also a plus.

Languages
ENGLISH
Level
Excellent

Additional Information
Benefits

Gross salary per year: 29100 €

Eligibility criteria

Candidates must hold a PhD in computer science, physics, mathematics, or in a related discipline, and have a strong publication record in their respective field. A solid mathematical background is required, as well as good programming skills in C++, Python and/or Matlab. Experience in Rendering techniques and/or Machine Learning is highly valued. Experience with Monte Carlo methods is also a plus.

Selection process

Selection will be based on the delivered documentation. In case of doubt, an interview of the candidate might be requested by the project IP.

Additional comments

Priority will be given to people with disabilities (Law 89/2015 of June 2, reserve of quota 2% in favour of people with disabilities in companies of 50 or more people).

Website for additional job details
https://seu.ub.edu/ofertaPublicaCategoriaPublic/listPublicacionsAmbCategoria?ca…

Work Location(s)

Number of offers available
1
Company/Institute
Department of Mathematics and Informatics
Country
Spain
City
Barcelona
Geofield

Where to apply

Website
https://seu.ub.edu/ofertaPublicaCategoriaPublic/listPublicacionsAmbCategoria?ca…

Contact

City
Barcelona
Website
https://www.ub.edu
Street
Gran Via de les Corts Catalanes, 585
Postal Code
08007

STATUS: EXPIRED

View or Apply
To help us track our recruitment effort, please indicate in your email – cover/motivation letter where (tendersglobal.net) you saw this job posting.

Share

Recent Posts

Information Management Officer (IMO) – NOA

tendersglobal.net DEADLINE FOR APPLICATIONS27 November 2024-23:59-GMT+03:00 East Africa Time (Mogadishu)WFP celebrates and embraces diversity. It…

8 minutes ago

Programme Policy Officer (Fortification/ SBN ) SC-9

tendersglobal.net DEADLINE FOR APPLICATIONS26 November 2024-23:59-GMT+07:00 Indochina Time (Vientiane)WFP celebrates and embraces diversity. It is…

8 minutes ago

UN·E CHARGÉ·E DE COLLECTE 360° AVEC UNE MAJEURE FACE-À-FACE FRANCE

tendersglobal.net A propos de : Action contre la Faim Créée en 1979, Action contre la Faim…

8 minutes ago

Financial Management Officer

tendersglobal.net Job Description Organizational Setting and Reporting RelationshipThe position of Financial Management Officer is assigned…

8 minutes ago

MTIT/BSS/PSU Consultant- Solutions Architect

tendersglobal.net --?xml version="1.0" encoding="UTF-8"?--> <-- Generated by Oracle BI Publisher 10.1.3.4.2 --> .c0 {line-height: 13.8pt;margin-top:…

8 minutes ago

MTIT/BSS/PSU Consultant- IT Project Manager

tendersglobal.net --?xml version="1.0" encoding="UTF-8"?-->   Organizational Setting   The Division of Information Technology provides support…

8 minutes ago
For Apply Button. Please use Non-Amp Version

This website uses cookies.