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Highly desirable:
• Metabolomics: Proficiency in Mass Spectrometry or NMR-based metabolic profiling and analysis.
• Systemic Interaction: Experience in studying the Immune System or the Nervous System.
• Expertise in designing and executing complex in vivo experiments. A strong background in developing, breeding, and analyzing genetically modified animal models applied to cancer biology or neuroscience.

Using mouse models and human iPSC system, together with scRNA/ATAC-seq technique to decipher the molecular mechanism for Neurodegeneration and Aging. We also aim to uncover the new method to cure motor neuron disease by gene therapy. We strongly encourage candidates interested in molecular mechanisms of gene regulation as related to non coding RNAs should apply. Candidates experienced in mouse experiments and ESC/iPSC cell culture are preferred, but not required.

辦理IACUC相關業務，落實執行IACUC效能

實驗動物飼育管理

1. Positions will entail independent projects in research topics spanning R-loop dynamics, genome organization, DNA damage repair, and cancer progression and drug resistance.
2. Perform molecular biology and cell biology experiments (e.g., tissue culture, CRISPR cloning, library preparation).
3. Conduct proteomics and genomics-related experiments.
4. Analyze sequencing and genomics data using Python and R
5. Assist in laboratory organization, inventory management, and ordering reagents.
1.本職位將進行獨立研究計畫，研究主題涵蓋 R-loop 動態、基因體結構、DNA 損傷修復，以及癌症進展與抗藥性等領域。
2.執行分子生物與細胞生物學實驗（如細胞培養、CRISPR 克隆、定序文庫製備等）。
3.進行蛋白質體學與基因體相關實驗。
4.使用 Python 或 R 進行定序資料與基因體數據分析。
5.協助實驗室日常管理（試劑訂購、庫存整理等）。

This project aims to elucidate the functions and evolution of transcription factors in diverse cell differentiation processes in plants. We are seeking a motivated individual who will proactively engage in experiments including cultivation of the model plant Arabidopsis thaliana, plant transformation, microscopy-based analyses, and transient reporter assays using Nicotiana benthamiana.

The candidate will also be expected to perform basic data analysis, including transcriptome and single-cell RNA-seq analyses, using tools such as Excel.

Prior experience in these research areas is not required. We are looking for someone who is eager to learn new techniques, communicates actively with lab members, and can independently drive research forward.

Developing single-cell assays and application; Integrating chemistry, materials and microfluidics for streamlined chemical synthesis; developing smart liposomes for cell-mimicking and biomedical application. For more information, please check our website- http://scellse.weebly.com/

[Bacterial Evolutionary Genomics] This position involves largescale comparative analyses of genome sequences to investigate genetic diversity and diversification across bacterial lineages. The research focuses on developing species delineation methods to improve taxonomic frameworks and identification accuracy, while also examining key genes associated with bacterial diversification to provide new insights into evolutionary and functional genomics. For related research projects and recent publications, please see our lab website: https://ipmb.sinica.edu.tw/chkuo/

The NanoBioPhotonics Laboratory (NBP Lab) is dedicated to developing advanced optical microscopy technologies and integrating them with chemical and biological techniques. Through interdisciplinary approaches, the lab quantitatively investigates nanoscale structures and dynamics in living cells. Responsibilities include optical system development, operation, and optimization, live-cell experiments, image and data analysis, execution of research projects, and publication of research results.

【工作內容 / Responsibilities】
本實驗室的研究重點為傳染病及癌症新藥研發，利用結構生物學的技術（X光結晶學，低溫電子顯微鏡）探討新冠肺炎、流感、抗藥性細菌感染以及癌細胞之膜蛋白及醣蛋白結構，作為新藥研發的基礎。
1、藉由分析蛋白質的立體空間結構，作為新藥設計的基礎。
2、運用細胞及動物實驗模型，探討新型藥物之廣度及效能。
My lab foucuses on structural biology and drug discovery in infectious diseases and cancers. X-ray crystallography and cryo-EM are being used to study membrane proteins and glycoproteins in SARS=COV-2, influenza viruses, drug-resistant bacteria and cancers, to provide structural basis for drug-discovery and vaccine design. In vitro cell based assays and in vivo animal models are being used to validate the efficacy of novel vaccines.

Research Focus:
Our laboratory focuses on neurodegenerative diseases, spinal muscular aging, and RNA biology. We investigate molecular mechanisms and regulatory networks underlying disease and aging processes by integrating multi-omics approaches. The lab maintains stable production of high-quality datasets to support long-term, biologically driven research programs.

Position Overview:
This is a research-oriented bioinformatics position responsible for extracting biologically meaningful insights from multi-omics datasets. The majority of the work involves customized analysis and biological interpretation, complemented by routine pipeline execution and workflow evaluation or optimization.
In recent years, our research program has increasingly emphasized single-cell multi-omics, spatial transcriptomics, and long-read sequencing to characterize cellular and molecular changes associated with aging and neurodegeneration.
Initial projects will be conducted in close collaboration with a senior bioinformatician, with the expectation of transitioning toward independent leadership of customized analyses within the first year.
This is a research-oriented bioinformatics position responsible for extracting biologically meaningful insights from multi-omics datasets. The majority of the work involves customized analysis and biological interpretation, complemented by routine pipeline execution and workflow evaluation or optimization.

Laboratory Strengths:
The laboratory provides stable access to high-quality multi-omics datasets and is led by a bioinformatician with over ten years of experience. Authorship is assigned based on actual contribution, and the lab maintains consistent publication output. Funding support is secured for at least five years, and the group sustains long-term domestic and international collaborations, offering a stable and growth-oriented research environment.

We conduct research in diverse areas of computational biology, data science and machine learning, including multi-omics data integration of cancers, optimal treatment design for heterogeneous and evolving tumors, single-cell omics data analysis, evolution of biomolecular networks and human populations, topological characterization of networks, and unsupverised learning using deep neural networks. Group members will gain experience in learning domain knowledge, performing scientific reasoning, formulating and solving mathematical models, developing algorithms, writing programs and using existing packages, collecting and analyzing big data, and interacting closely with international and domestic collaborators. We look for motivated persons curious about open scientific problems and willing to dedicate energy and time to solve them.