24小时热门版块排行榜

>论坛更新日志 (3228)
>虫友互识 (827)
>文献求助 (222)
>休闲灌水 (157)
>导师招生 (151)
>考博 (130)
>教师之家 (86)
>硕博家园 (80)
>博后之家 (77)
>找工作 (77)
>论文投稿 (74)
>论文道贺祈福 (67)
>基金申请 (65)
>考研 (57)
>公派出国 (51)
>招聘信息布告栏 (33)

返回列表

【有奖交流】积极回复本帖子，参与交流，就有机会分得作者 cnzhan 的 57 个金币，回帖就立即获得 1 个金币，每人有 3 次机会

cnzhan

新虫 (小有名气)

应助: 8 (幼儿园)
金币: 923.2
帖子: 111
在线: 50.1小时
虫号: 1161266

[交流] 澳大利亚国立大学（全球30名）全奖：使用具身智能及机器学习开发下一代光伏材料【急】

项目名称: 使用具身智能及机器学习开发下一代光伏材料（请联系hualin.zhan@anu.edu.au申请）

院校: 澳大利亚国立大学计算机及工程学院

入学时间: 2025年3月31日前（获得全奖无额外要求）或2025年8月31日后（获得全奖有额外要求）

学生专业要求：计算机（全年接收申请）
数学、物理、半导体（接收8月31日后入学申请）

奖学金信息（全奖）：
生活费：每年 AUD$38,154 （人民币约17万9千）
学费：免费（必须达到以下第1点硬性要求）

奖学金要求：
1. 硬性要求（适用于所有申请者）：
GPA > 3.2/4
毕业院校：211或985或双一流（一般本科不低于211，达到额外要求者可特殊考虑）
2. 额外要求（适用于8月31日后入学）：
达到以下要求之一即可。申请者须为一作或共一
2.1 发表本领域内至少1篇高影响力论文（影响因子>20）
2.2 至少1篇高影响力会议论文（见附表）
2.3 至少3篇高质量论文（影响因子>5）
2.4 至少3份专利

项目导师:
Dr Hualin Zhan（本项目主导师，澳大利亚先进光伏中心 ACAP Fellow）
邮件： hualin.zhan@anu.edu.au
Prof Kylie Catchpole（本项目博士生Chair，澳大利亚科学院及工程院双院士）

注意：该项目需要经常往返堪培拉（澳大利亚国立大学）及墨尔本（莫纳什大学）。旅行经费由项目提供。

项目介绍:

We are a world-leading group in the field of photovoltaics. Our world-record perovskite solar cells have identified great opportunities and key challenges to revolutionize the next-generation photovoltaics (publications in nature, science, energy environ. Sci., etc.). This project aims to address these key challenges, in which we will use machine learning to deliver a step-change in the field’s capacity to precisely control the stability of perovskite and to rationally design the perovskite-based solar cells. We have already developed a prototype machine learning platform that is ideal for future PhD studies on this project (recently published in Energy Environ. Sci.).

Successful candidates will work in a friendly environment with access to world-class photovoltaics fabrication, characterization, and computation facilities, such as the Australian Centre for Advanced Photovoltaics, Australian National Fabrication Facility, National Computational Infrastructure, etc. The act nodes of these facilities are all hosted by the Australian National University. Candidates will have opportunities to visit our close collaborators in Germany, United States, China, and other states in Australia. Candidates are expected to attend domestic and international conferences. Project-funded students must visit Monash University regularly (travel costs will be covered).

Candidates with a keen interest in technological revolution of perovskite photovoltaics using embodied AI and machine learning are encouraged to apply. Experience in machine learning, mathematics, physics, and/or perovskite materials engineering is highly preferred. If you are passionate about engineering science and impactful research, we invite you to apply for this exciting opportunity to shape the future of sustainable energy technologies.

Selected publications:

H. Zhan, et. al., Energy Environ. Sci., 2024, 17, 4735-4745.

J. Peng, et. al., Nature, 2022, 601, 573-578.

J. Peng, et. al., Science, 2021, 371, 390.

H. Shen, et. al., Energy Environ. Sci., 2018, 11, 394-406.

附表：高影响力会议
Publication h5-index h5-median
1. Neural Information Processing Systems 337 614
2. International Conference On Learning Representations 304 584
3. International Conference On Machine Learning 268 424
4. AAAI Conference On Artificial Intelligence 220 341
5. Expert Systems With Applications 165 228
6. IEEE Transactions On Systems, Man And Cybernetics Part B, Cybernetics 155 212
7. IEEE Transactions On Neural Networks And Learning Systems 149 215
8. Neurocomputing 136 210
9. International Joint Conference On Artificial Intelligence (Ijcai) 136 192
10. Neural Computing And Applications 135 184
11. Information Fusion 134 214
12. Applied Soft Computing 133 171
13. Knowledge-Based Systems 126 198
14. Artificial Intelligence Review 118 198
15. Journal Of Machine Learning Research 117 202
16. IEEE Transactions On Fuzzy Systems 111 160
17. International Conference On Artificial Intelligence And Statistics 100 162
18. Engineering Applications Of Artificial Intelligence 97 135
19. Neural Networks 95 146
20. Conference On Robot Learning 88 150

回复此楼