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Responsibility: (either)
(1) Exploring epigenetic control in shaping sexual dimorphic circuit.
(2) Exploring the neural circuit mechanisms through Drosophila olfactory virtual reality system
(3) Exploring circuit integration of thermo-, hygro-, and olfactory sensation.

誠徵對新興傳染病症研究有熱誠的研究人員

Institute of Information Science at Academia Sinica, in collaboration with National Taiwan University, is seeking motivated Research Assistants to work on cutting-edge computer vision and deep learning projects. This position offers a unique opportunity to conduct research under the joint supervision of Prof. Chun-Yi Lee (NTU) and Dr. Chien-Yao Wang (Academia Sinica).

The selected candidate will engage in advanced research projects at the intersection of computer vision and deep learning, with a minimum commitment of eight months. This position is ideal for candidates planning to pursue academic careers or graduate studies abroad, offering valuable research experience and publication opportunities.

Our research team is seeking 1 or 2 master’s-level Research Associates to join us in exploring the evolution, ecology and biology of eukaryotic microbes with key roles on Earth. We focus on the interactions between microbes and their environment and utilize cutting-edge omics and bioinformatics tools to uncover their evolutionary trajectories and regulatory mechanisms. The position is opened until filled.


顧銓研究室誠徵1 至 2 名碩士級研究助理，一同探索在地球上扮演重要角色的真核微生物之演化、生態與生物學。我們專注於微生物與環境的互動，並運用最先進的體學與生物資訊工具，以發掘其演化軌跡與調控機制。該職缺將開放至額滿為止。


Job description (at least three of the tasks listed below):

- Culturing and maintaining microalgal and protist strains

- Nucleic acid extraction, NGS library preparation and sequencing

- Single-cell omics analysis

- Bioinformatic analyses, including genome assembly, annotation, phylogenomic analysis, etc.

- Giant virus isolation and characterization

- Other routine laboratory affairs and assigned tasks



工作內容（至少三項任務）：

- 培養與維持微藻及原生生物菌株

- 核酸萃取、NGS建庫與定序

- 單細胞體學分析

- 生物資訊分析，包括基因體組裝、註解、親緣基因體學分析等

- 巨病毒分離與特性分析

- 其他實驗室例行事務與交辦事項

Join the "Climate Change and Environmental Studies" research group team. Under the guidance of the project leader/co-leader, complete tasks such as data cleaning, statistical modeling, data analysis, and publish research findings in international journals.

Team Members: Academician Ruey Tsay (University of Chicago), Dr. Su-Yun Huang (ISS-AS), Dr. Ting-Li Chen (ISS-AS), Dr. Ming-Chung Chang (ISS-AS), Dr. Hsueh-Han Huang (ISS-AS), Professor Jeng-Min Chiou (NTU), Professor Chun-Hao Yang (NTU)

The research interest in our lab is to study the post-transcriptional gene regulation with the approaches of genomics and molecular biology. The projects will focus on RNA splicing, translation and stability. Using human cell lines as our major model system, and combining computational biology, molecular biology and next-generation sequencing, we aim to understand how sequence variations contribute to post-transcriptional regulation in diseases.

Position summary:
We seek for a highly motivated research assistant to join the Marine Evo-Evo-Devo laboratory of Vincent Laudet’s Unit at the ICOB’s Marine Research Station at Yilan (https://groups.oist.jp).

The Center for Survey Research, Research Center
for Humanities and Social Sciences (RCHSS) in
Academia Sinica, Taiwan is looking for motivated
candidates specializing in survey methods,
computational social science, text mining, and data
science to join the Center. We are an
interdisciplinary team of social scientists and data
science researchers with the goal of integrating
different research methods to advance
understanding of human behaviors and social
issues. We invite applications from outstanding
candidates for the tenure-track position at the
Assistant, Associate, or Full Research Fellow level
(equivalent to Assistant, Associate, or Full
Professors, respectively, at university).

Research on Optimization of Deep Learning Model Inference and Training

The Computer Systems Laboratory - Machine Learning Systems team focuses on research areas including parallel and distributed computing, compilers, and computer architecture. We aim to leverage computer system technologies to accelerate the inference and training of deep learning models and develop optimizations for next-generation AI models. Our research emphasizes the following:

1. AI Model Compression and Optimization
Model compression techniques (e.g., pruning and quantization) reduce the size and computational demands of AI models, which are crucial for resource-constrained platforms such as embedded systems and memory-limited AI accelerators. We aim to explore:
* AI compiler: deployment methods for compressed models across servers, edge devices, and heterogeneous systems.
* High performance computing: efficient execution of compressed models on processors with advanced AI extensions, e.g., Intel AVX512, ARM SVE, RISC-V RVV, and tensor-level accelerations on GPUs and NPUs.

2. AI Accelerator Design
We aim to design AI accelerators for accelerating AI model inference, focusing on software and hardware co-design and co-optimization.

3. Optimization of AI Model Inference in Heterogeneous Environments
Computer architectures are evolving toward heterogeneous multi-processor designs (e.g., CPUs + GPUs + AI accelerators). Integrating heterogeneous processors to execute complex models (e.g., hybrid models, multi-models, and multi-task models) with high computational efficiency poses a critical challenge. We aim to explore:
* Efficient scheduling algorithms.
* Parallel algorithms for the three dimensions: data parallelism, model parallelism, and tensor parallelism.

Area(s) of Specialization:
Indigenous/Public Archaeology: Preference shall be given to applicants who have conducted archaeological research predominantly in Taiwan, have experience in archaeological site surveys and excavations, and have demonstrated success in advancing public archaeology and/or collaborating with indigenous peoples.

地理人工智慧 (GeoAI)、地理計算(Geo-Computing)或計算社會科學(Computational Social Science) 等地理資訊科學相關領域研究

The applicant should specialize at least one of the following fields: (1) GeoAI; (2) Geo-Computing; (3) Computational Social Science; or, (4) Geographic Information Science related research.