CakeResume 找人才
最輕量、快速的招募方案，數百家企業的選擇
搜尋履歷，主動聯繫求職者，提升招募效率。
- 瀏覽所有搜尋結果
- 每日可無限次數開啟陌生對話
- 搜尋僅開放付費企業檢視的履歷
- 檢視使用者信箱 & 電話
職場能力評價定義
李兆峻 George
Yuan Ze University
Taipei，TW
Experience
ASUS，2020 / 9 - Present
Software Engineer, Backend Engineer
1. API development (python, Django, DRF, unittest, channel)
According to the user's request, design and develope appropriate API.
2. Version control (Gitlab, Gitlab-ci)
Maintain and improve CI/CD flow on Gitlab. Automatically deploy the latest project.
3. System management (Nginx, Supervisor, Daphne, Gunicorn)
Nginx for managing system network. Supervisor for run asgi and wsgi system at the same time, run wsgi system via Gunicor, run asgi system via Daphne.
FEMH，2020 / 7 - 2020 / 9
Data Engineer, database management and integration of data from different sources to provide users.
ROCMC，2019 / 9 - 2019 / 12
Served in Taiwan's military, Marine Corps.
Nuuo intern，2016 / 2 - 2016 / 9
As a research and development intern in Nuuo.
Education
Yuan Ze University，2017 / 9 - 2019 / 7
Master of Computer Science
Yuan Ze University，2012 / 9 - 2017 / 7
Bachelor of Computer Science
Skills
Programing
Python
C#
PHP
C
Relevant Course
Django + DRF
Devops (Gitlab, Azure)
Sql
Linux
Jenkins
Tableau
Language
Chinese (native)
English (Toeic - 620 (2015/06))
Thesis
Identification and Characterization of Cancer Driver Mutation Affecting Post-translational Modification
We collect cancer mutations and human experimental PTM sites, and then we use several computational approaches to identify cancer driver genes and driver mutations. Next, we detect PTM sites around driver mutations. We will recognize disease mechanism through PTM related driver mutations.
Project
dbPTM
dbPTM is a database aims to provide functional and structural analyses for post-translational modifications (PTMs). I integrate the association of PTMs and nsSNPs for the database. We can understand diseases through these associations.
PMID: 30418626
dbPTMut
dbPTMut uses 4 computational tools to identify cancer driver genes. And use 1 tool to identify driver mutations on the driver genes that were detected by previous step. Next, dbPTMut finds the same position of the Post-translational modification (PTM) site and driver mutation on the protein sequence.
李兆峻 George
Yuan Ze University
Taipei，TW
Experience
ASUS，2020 / 9 - Present
Software Engineer, Backend Engineer
1. API development (python, Django, DRF, unittest, channel)
According to the user's request, design and develope appropriate API.
2. Version control (Gitlab, Gitlab-ci)
Maintain and improve CI/CD flow on Gitlab. Automatically deploy the latest project.
3. System management (Nginx, Supervisor, Daphne, Gunicorn)
Nginx for managing system network. Supervisor for run asgi and wsgi system at the same time, run wsgi system via Gunicor, run asgi system via Daphne.
FEMH，2020 / 7 - 2020 / 9
Data Engineer, database management and integration of data from different sources to provide users.
ROCMC，2019 / 9 - 2019 / 12
Served in Taiwan's military, Marine Corps.
Nuuo intern，2016 / 2 - 2016 / 9
As a research and development intern in Nuuo.
Education
Yuan Ze University，2017 / 9 - 2019 / 7
Master of Computer Science
Yuan Ze University，2012 / 9 - 2017 / 7
Bachelor of Computer Science
Skills
Programing
Python
C#
PHP
C
Relevant Course
Django + DRF
Devops (Gitlab, Azure)
Sql
Linux
Jenkins
Tableau
Language
Chinese (native)
English (Toeic - 620 (2015/06))
Thesis
Identification and Characterization of Cancer Driver Mutation Affecting Post-translational Modification
We collect cancer mutations and human experimental PTM sites, and then we use several computational approaches to identify cancer driver genes and driver mutations. Next, we detect PTM sites around driver mutations. We will recognize disease mechanism through PTM related driver mutations.
Project
dbPTM
dbPTM is a database aims to provide functional and structural analyses for post-translational modifications (PTMs). I integrate the association of PTMs and nsSNPs for the database. We can understand diseases through these associations.
PMID: 30418626
dbPTMut
dbPTMut uses 4 computational tools to identify cancer driver genes. And use 1 tool to identify driver mutations on the driver genes that were detected by previous step. Next, dbPTMut finds the same position of the Post-translational modification (PTM) site and driver mutation on the protein sequence.