Job summary
Job post source
This job is directly from Academia Sinica, Taiwan
Job overview
The Research Specialist role at Academia Sinica supports faculty research through data mining, knowledge extraction, and data analysis to advance social science studies using big data and AI.
Responsibilities and impact
The specialist will analyze online public opinion, apply AI and big data methods in social science research, and develop computational systems to enhance knowledge sharing and social impact.
Compensation and benefits
Compensation and benefits follow Academia Sinica regulations, including government civil servants' insurance and retirement system coverage.
Experience and skills
Applicants should have a doctoral degree preferred in Information Science, Data Science, Social Science, Statistics or related fields, with skills in AI methods like computer vision and NLP, data structures, database technologies, and research project management.
Work environment and culture
The work environment follows Academia Sinica's operating hours and regulations, emphasizing academic research enthusiasm, creativity, and strong communication skills.
Company information
Academia Sinica is a leading research institution in Taiwan focused on humanities and social sciences, providing a platform for advanced academic research and knowledge dissemination.
Team overview
The position is within the Research Center for Humanities and Social Sciences, collaborating with faculty members and researchers at the Center for Survey Research.
Job location and travel
The job is located at the Center for Survey Research, Research Center for Humanities and Social Sciences, Taipei, Taiwan, with standard operating hours.
Application process
Applicants must submit a detailed CV, degree certificates, transcripts, thesis, publications, and three recommendation letters by August 31, 2025, via email to the contact provided.
Unique job features
The role uniquely integrates big data analytics and AI in social science research, offering opportunities to develop computational systems that impact knowledge sharing and social influence.
Company overview
Academia Sinica, Taiwan's premier research institution, is dedicated to advancing knowledge across a wide range of disciplines, including natural sciences, life sciences, and humanities and social sciences. Established in 1928, it operates as an independent research organization under the government, fostering interdisciplinary collaboration and supporting academic excellence. The institution generates revenue primarily through government funding, research grants, and partnerships with global academic and industrial entities. Its significant contributions to scientific innovation and policy development make it a cornerstone of Taiwan's intellectual and technological progress.
How to land this job
Position your resume to emphasize your expertise in data mining, knowledge extraction, and data analysis within social sciences, highlighting any experience with big data analytics and AI methods such as natural language processing or computer vision.
Highlight your academic credentials, especially a doctoral degree if applicable, and detail your technical skills in AI, data structures, and database technologies relevant to the Research Specialist role at Academia Sinica.
Apply through multiple channels including the official Academia Sinica website and LinkedIn to maximize your chances of visibility and consideration for the position.
Connect with current researchers or staff in the Research Center for Humanities and Social Sciences at Academia Sinica on LinkedIn, using ice breakers like asking about recent projects on online public opinion analysis or expressing interest in their computational systems development.
Optimize your resume for ATS by incorporating keywords from the job description such as 'big data analytics,' 'artificial intelligence,' 'natural language processing,' 'data mining,' and 'social science research' to ensure it passes automated screenings.
Utilize Jennie Johnson's Power Apply feature to automate tailored applications, identify the best application channels, and find relevant LinkedIn contacts to network with, allowing you to focus more on preparing for interviews and research discussions.
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