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瑞士洛桑联邦理工学院2021年招聘博士后职位(风险分析和优化实验室的最优化)

发布时间:2021-11-09 09:47信息来源:瑞士洛桑联邦理工学院

瑞士洛桑联邦理工学院2021年招聘博士后职位(风险分析和优化实验室的最优化)

Postdoctoral Position In Mathematical Optimization In The Risk Analytics And Optimization Lab

EcolePolytechniqueFederale De Lausanne (EPFL)

Description

EPFL, the Swiss Federal Institute of Technology in Lausanne, is one of the most dynamic university campuses in Europe and ranks among the top 20 universities worldwide. The EPFL employs more than 6,000 people supporting the three main missions of the institutions: education, research and innovation. The EPFL campus offers an exceptional working environment at the heart of a community of more than 16,000 people, including over 12,000 students and 4,000 researchers from more than 120 different countries.

Postdoctoral Position in Mathematical Optimization in the Risk Analytics andOptimization Lab

Your mission :

The Risk Analytics and Optimization (RAO) lab at the EcolePolytechniqueFédérale de Lausanne (EPFL) led by Prof. Daniel Kuhn is seeking applications for a postdoctoral position in the area of optimization under uncertainty, in particular in the fields of (distributionally) robust optimization and stochastic programming, with applications to energy systems. The successful candidate will conduct research aiming to design and optimize drone operations at Swissgrid, the Swiss national electricity grid operator. Swissgrid is responsible for the operation, safety and expansion of the Swiss transmission grid. As the operator of a critical infrastructure, Swissgrid insists on a high level of safety and reliability. Keeping the transmission system stable, safe and secure takes seamlessly operating infrastructure, continuous management of power flows and cooperation with partners. Swissgrid is actively testing drones to improve the efficiency of maintenance and, as a consequence, the safety of its system, it's employees and the public. For this reason, Swissgrid aims to develop a mathematical optimization model that supports strategic decision-making. The model will help to understand how drones can be effectively deployed for line inspection and for diverse applications including, but not limited to, regular planned monitoring of the infrastructure.

Main duties and responsibilities include :

Contribute to defining, solving and testing a data-driven mathematical optimization model to support strategic decision-making at Swissgrid;

Interact with the end-users of the model at Swissgrid at all stages of the project; Document the model and its assumptions as well as limitations, and ensure the reproducibility of its results;

Contribute to the research and teaching efforts of the RAO lab, interacting with MSc and PhD students and senior researchers.

Your profile :

Applicants must hold a PhD in a quantitative field and have a strong publication record in mathematical optimization. They also need to have experience in working with optimization software. Experience in stochastic programming or (distributionally) robust optimization is particularly valuable.

We offer :

We offer excellent working conditions and state-of-the-art infrastructure in a dynamic international environment at the forefront of research. The position comes with a competitive salary. The project offers the combination of an academically challenging research question and a novel high-impact industrial application in collaboration with Swissgrid.

More information about our lab can be found on our website: https: // www. epfl.ch/labs/rao/.

Start date : The position is available immediately and the start date is flexible.

Applications should include a motivation letter and the candidate's CV as pdf documents as well as the contact information of three references.

Applications are accepted until the position is filled.

Term of employment : Fixed-term (CDD)

Duration : 1 year, renewable depending on the progress of the project

Contact :

Remark : Only candidates who applied through EPFL website or our partner Jobup's website will be considered. Files sent by agencies without a mandate will not be taken into account.

Reference : Job Nb 2084

apply online

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