Consultant, Networking (4 months project)

Job Description

CTO/AIBD/CLOUD/C428/190924

Job Responsibilities

Scope of Consultancy Services:
  • Weekly consultancy in the algorithm design, mathematical modeling of machine learning, mobile applications, and performance analysis of system on Industrial IoT Platform survey and evaluation
  • Study and suggest new algorithmic or system enhancement which may lead to patentable results on Fog Computing in smart water
  • Review general algorithm, design, and architecture for machine learning platform and the modules; suggest potential performance benchmark model and methodology for improvement
  • Consultancy on machine learning, networking, Internet, etc industry direction and academic research scope. Help formulate and focus ASTRI R&D direction
Deliverables:
  • To speed up of the development process and leverage existing expertise and know-how in IoT networking in the following potential areas:
  1. Industrial IoT Platform survey and evaluation;
  2. Fog Computing in smart water.
  • Three Technical lectures related to Industrial IoT and evaluation
  1. Technical trend on Industrial IoT
  2. Data generation and evaluation
  3. Generate an algorithm design, mathematical modeling of Fog Computing
  • Solving the technical problems, which includes checking algorithm results, finding out the cause of the problem and improvement solution and providing a final report for the requirement
  1. Industrial IoT Platform survey
  2. Fog Computing in smart water

Requirements

  • Ph.D. Degree in Applied Mathematics or related disciplines
  • 15+ years of active research experience in HiTech companies or Internet related research
  • Both industry and academic research experience is highly preferred; can understand the requirement, formulate the problem, and propose innovative solutions addressing the problem effectively
  • Strong mathematical modeling and performance analysis capability including Internet content distribution, data-driven modeling and analysis of large scale systems.
  • Good understanding and appreciation of algorithmic level fine tuning versus system-level performance optimization – various tradeoff, parameters, adjustment, and modeling effects etc.
  • Broad knowledge and connection in the community – keep abreast of the state of art of the latest progress, other industry players approach and academic R&D direction.

Application

Interested candidates please send application (quoting Ref. No.) with detailed resume, current and expected salary to Talent Acquisition via email to  [email protected]  

Application open until 2 October 2019.

Only short-listed candidates will be notified. ASTRI reserves the right not to fill the position.

ASTRI is an Equal Opportunities Employer. Personal data provided by job applicants will be used exclusively for recruitment only.