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Postdoctoral positions in Brain Dynamics / Computational Neuroscience (Chile–Spain)
by Wael El Deredy Jan. 5, 2026

Jan. 5, 2026

Help Shape the Future of Stroke Rehabilitation and Brain Stimulation We invite applications to join the Brain Dynamics Lab—an interdisciplinary research team at the interface of dynamical systems theory, brain network modelling, and neurostimulation-based rehabilitation. Our mission is to uncover and exploit the mechanisms of brain plasticity following stroke and neuromodulation, by combining cutting-edge modelling with real-world neurotechnology. We regard recovery not as anatomical repair, but as a problem of restoring network-level brain dynamics through non-invasive electrical stimulation (tDCS/tACS). We model the brain as a dynamical system perturbed by lesion, reconfigurable via stimulation-dependent plasticity. Paid positions according to the academic level Location: Valencia, Spain Chile [Valparaiso, Santiago, Talca, Concepción, flexible within collaborating institutions] Positions Available: • PhD studentships [2 years] • Postdoctoral research fellows • Research assistants (MSc-level support roles) Fields: Physics, Biomedical Engineering, Electronics/Telecom/Control/Informatics Engineering, Applied Mathematics, Computer Science, Computational Neuroscience What You’ll Work On Successful applicants will join a growing team working on projects including: • Whole-brain network modelling (Kuramoto, Wilson-Cowan, neural mass models) to simulate post-stroke disruption and plastic recovery • Computational modelling of plasticity mechanisms (Hebbian, homeostatic, STDP, resonance-tuned) across varying brain states • Control theory in brain networks, including stimulation as control input to re-establish metastability and synchrony • Analysis of electrophysiological and imaging data (EEG, TMS, lesion mapping) from healthy and clinical populations • Development of simulation-guided protocols for individualized, state-dependent stimulation These positions will support Masters or PhD theses, contribute to postdoctoral innovation, and underpin a translational pipeline from virtual lesion modelling in healthy participants to patient-specific neurorehabilitation strategies. We are looking for: We welcome candidates from a broad range of backgrounds, including: • Physicists with expertise in nonlinear dynamics or network theory • Electrical or Telecom Engineers with skills in signal processing, control theory, modelling, or brain–computer interfaces • Biomedical Engineers experienced in neuroimaging, neurorehabilitation, or neural interfaces • Applied Mathematicians or Computer Scientists with interests in simulation, control or computational neuroscience We value curiosity, collaboration, and a commitment to translational science. Programming skills in Python, Matlab or C++ are required. Prior experience with neural modelling (e.g., Kuramoto, neural masses), data analysis (EEG/fMRI), high performance computing (HPC), or brain stimulation (tDCS/tACS/TMS) is a strong plus but not required. Why join us now This is an exciting moment in the field. Advances in connectome-informed modelling, network control theory, and neuromodulation are converging to make precision neurostimulation a clinical reality. As part of our team, you’ll be at the frontier of: • Designing next-generation rehabilitation tools • Validating models with real-world clinical and experimental data • Publishing in top-tier journals (e.g., Network Neuroscience, Neuroimage, PLOS Comp Biol) • Collaborating with international partners in Spain, Portugal, Chile, and the UK How to apply Send academic CV and one page letter of motivation describing your research interests, and fit with the Brain Dynamics Lab to: Chile Alejandro.Weinstein(a)USM.cl<mailto:Alejandro.Weinstein@USM.cl> Spain Wael.Deredy(a)ValgrAI.EU<mailto:Wael.Deredy@ValgrAI.EU> Selected group publications https://arxiv.org/abs/2511.14065 https://www.biorxiv.org/content/10.1101/2025.04.30.651283v2.abstract https://www.nature.com/articles/s41598-025-27606-5 https://www.nature.com/articles/s41598-025-14299-z https://ieeexplore.ieee.org/abstract/document/10937758/ https://doi.org/10.1098/rstb.2023.0093 https://link.springer.com/article/10.1007/s11571-024-10093-1

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ICPRAI 2026: Special Session on Frontiers of Artificial Intelligence for Medical Applications: Models, Reasoning, Perception, and Interaction
by Ghazaleh Khodabandelou Jan. 4, 2026

Jan. 4, 2026

Special Session on Frontiers of Artificial Intelligence for Medical Applications: Models, Reasoning, Perception, and Interaction ICPRAI 2026, Montréal, Québec, Canada, June, 2026 https://icprai2026.com/ Scope Artificial intelligence has seen remarkable progress in digital healthcare across areas such as learning algorithms, knowledge representation, perception, and interaction. From deep learning advances in vision and language, to reinforcement learning for control, to symbolic and neuro-symbolic hybrids for robust reasoning, modern AI systems are increasingly capable of understanding complex data, adapting to new tasks, and interacting with humans and environments. This Special Session invites original contributions that explore foundational models, architectures, and applications spanning the AI spectrum, including but not limited to learning and representation; planning and decision-making; perception and multimodal understanding; human-AI collaboration; and trustworthy, explainable, and ethical AI. We welcome theoretical analyses, novel algorithms, system implementations, and domain-specific studies that illustrate state-of-the-art techniques and future directions in AI, with special encouragement for work in large language models, multimodal vision-language modeling, and impactful applications in healthcare and medical domains such as medical imaging, autism detection, neurodegenerative disorders (e.g., Alzheimer’s and Parkinson’s), and diabetes management. Topics of Interest Topics of interest include, but are not limited to: • Large Language Models (LLMs) and foundation models • Embeddings, representation learning, and transfer learning • Generative modeling: GANs, VAEs, diffusion and beyond • Multimodal integration: vision-language, audio-visual, sensor fusion • Symbolic, neuro-symbolic, and hybrid reasoning systems • Automated planning, scheduling, and decision-theoretic frameworks • Reinforcement learning, multi-agent systems, and control • Human-AI collaboration, mixed-initiative interfaces, and personalization • Explainability, interpretability, causal analysis, and fairness • Robustness, safety, trustworthiness, and privacy-preserving AI • Healthcare and medical AI applications: imaging, diagnostics, chronic care 1 Important Dates • Full paper submission deadline: January 15, 2026 • Notification of acceptance: March 7, 2026 • Camera-ready deadline: March 13, 2026 • Early Registration deadline: until April 30, 2026 • Special Session at ICPRAI: June 15-18, 2026 Submission Guidelines Please follow the standard ICPRAI submission instructions at the conference website. When up loading your paper, select “Frontiers of Artificial Intelligence for Medical Applications: Models, Reasoning, Perception, and Interaction ” as the target session. Organizers • Prof. Ghazaleh Khodabandelou, University Paris-Est, France ghazaleh.khodabandelou(a)u-pec.fr<mailto:ghazaleh.khodabandelou@u-pec.fr> • Prof. Mounîm A. El Yacoubi, Institut Polytechnique de Paris, France mounim.el_yacoubi(a)telecom-sudparis.eu<mailto:mounim.el_yacoubi@telecom-sudparis.eu>

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Project Research Scientist Position at IIT Ropar.
by Sukrit Gupta Jan. 4, 2026

Jan. 4, 2026

Dear all, we are hiring a Project Research Scientist (Non Medical) at IIT Ropar for an ICMR project. Our lab does work with clinicians at multiple public hospitals in North India and this project is in collaboration with clinicians at PGIMER, Chandigarh. The project is funded for five years. Would prefer someone who has a computer science or AI background. Detailed advertisement at https://www.iitrpr.ac.in/downloads/sites/default/files/December/AD-01.pdf The selected candidate will be expected to enroll for a PhD at IIT Ropar. If you're interested you can drop me an email at sukrit.gupta(a)iitrpr.ac.in Deadline for application is: 10 January, 2026. Regards, Sukrit ________________ Sukrit Gupta, BEng (CS, PEC, India), PhD (CS, NTU, Singapore) Assistant Professor, Department of Biomedical Engineering, and School of Artificial Intelligence and Data Engineering, Indian Institute of Technology, Ropar, Punjab, India. Office: Room No. BM 28, Super Academic Block, IIT Ropar. Phone: +91 1881 232170, E: sukrit.gupta(a)iitrpr.ac.in, W: https://sites.google.com/site/sukritsite *God, grant me the serenity to accept the things I cannot change, the courage to change the things I can, and the wisdom to know the difference.*

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What can you do with 1000 neurons? Task 3
by Nicolas P. Rougier (inria) Jan. 4, 2026

Jan. 4, 2026

Dear all, The second task (cued decision) is still unsolved but the the challenge is still running with a new task (valued decision) as well as a new agenda. You'll find instructions at https://github.com/rougier/braincraft and the rules for the new task. Reminder: you have have 1000 neurons (leaky rate models), 100 seconds of training time and 10 runs for evaluation. The difficulty comes from the imposed constraints. Best, Nicolas Rougier. -- Nicolas P. Rougier —— www.labri.fr/perso/nrougier Institute of Neurodegenerative Diseases, Bordeaux

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Special Issue: Bio-Inspired Computation Based on Mathematical Modeling—Theories and Applications in Health Sciences
by Barna Iantovics Jan. 4, 2026

Jan. 4, 2026

Call for papersSpecial Issue: Bio-Inspired Computation Based onMathematical Modeling—Theories and Applications in Health SciencesJournal: Mathematics (ISSN 2227-7390) Impact Factor 2.2Submission https://www.mdpi.com/journal/mathematics/special_issues/9B5062KZ98 Dear Colleague, You are kindly invited to contribute with a paper to theSpecial Issue. It is estimated that biological life that has evolved overmillions of years will be a fruitful source of inspiration for the developmentof novel computational mathematical methods in the years to come, representingimportant research directions on mathematical modeling in the field ofartificial intelligence. Diverse problems in health sciences are computationally hardand cannot be solved efficiently via actual methods. Mathematical modelingbased on bio-inspired computing applied to solve computationally hard problemsin health sciences domains is an emerging field in this area. Bio-inspiredcomputing has been proven successful for solving a large variety of problems indomains of science where other methods have not been so effective. In this context, this Special Issue invites researchers tocontribute original works regarding the development of bio-inspiredcomputational and hybrid methods for solving difficult problems in healthsciences that represent significant scientific advancements. Kind regards,Guest EditorsProf. Dr. Laszlo Barna IantovicsProf. Dr. Matthias DehmerProf. Dr. Francesco FlamminiProf. Dr. Frank Emmert-Streib

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Call for papers - Special Issue: Advances in Intelligent Systems, Technologies and Applications
by Barna Iantovics Jan. 4, 2026

Jan. 4, 2026

Call for papersSpecial Issue: Advances inIntelligent Systems, Technologies and ApplicationsJournal: Applied Sciences (ISSN2076-3417) Impact Factor 2.5Submission https://www.mdpi.com/journal/applsci/special_issues/5IQ6DOHB42 Dear Colleague, You are kindly invited tocontribute with a paper to the Special Issue. Intelligence in nature is verydiverse; it can be discussed in terms of the intelligence of chimps, dolphins,and many other animals and even the collective intelligence of very simple lifeforms such as ants. The concept of intelligence is being adopted in manydomains of science. From practical and theoreticalperspectives, an essential current research direction that is under examinationby a very large number of scientists worldwide is the development of artificialsystems, also called agent-based systems, which can be either individual agentsor cooperative multiagent systems. These systems are embedded in theenvironment, possess a certain degree of autonomy, and are capable ofperceiving the environment and executing actions in it. Intelligence inagent-based systems can emerge through advanced problem-solving abilities. Todevelop these intelligent systems, techniques such as supervised learning andunsupervised learning play pivotal roles. Supervised learning involves trainingsystems on labeled datasets, enabling them to map inputs to outputs and improvetheir predictions or classifications over time. These methods are extensivelyused in applications such as image recognition, natural language processing,and medical diagnosis. On the other hand, unsupervised learning enables systemsto identify patterns and structures in unlabeled data, facilitating clustering,anomaly detection, and exploratory data analysis. A more recent paradigm,retrieval-augmented generation (RAG) and cache-augmented generation (CAG),combines retrieval- and cache-based methods with generative models to enhanceintelligent systems, producing highly contextualized and accurate responses oractions. These approaches are instrumental in developing advanced systems fordomains such as conversational AI, knowledge management, and decision support.Intelligent agent-based systems have many real-world applications, includingthe health sciences and industry. The number and diversity of intelligentsystems are increasing rapidly. In this context, the great challenge consistsof creating increasingly intelligent systems. Another critical challenge,approached by only a few researchers worldwide, is the development of universalmetrics, including black-box-based intelligence metrics, to measure theintelligence of these systems. Such advances could allow for the comparison ofsystems based on their intelligence. In cooperative multiagent systems,intelligence can be assessed at the system level; this is known as collectiveintelligence. Even in very simple cooperative multiagent systems, agents mayinteract nonlinearly at various decision points, resulting in emergentcomplexity and intelligence at the system level. This Special Issue aims toestablish a solid foundation for future research through a collection of papersthat advance the field by elaborating on theories, designing applications, andpresenting surveys regarding the next generation of increasingly intelligentsystems. The areas of research covered in these papers could include the studyof self-organization, emergence, hybridization, scalability, robustness,measuring machine intelligence, and the integration of advanced paradigms suchas supervised learning, unsupervised learning, retrieval-augmented generation,and cache-augmented generation. Kind regards,Guest EditorsProf. Dr. Laszlo Barna IantovicsProf. Dr. László KovácsDr. Attila Biró

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Fwd: [seminar.wwtns] World wide VVTNS series (6th season): Wednesday, January 7, 2025, at 11:00 am ET - Carlos Brody, Princeton Neuroscience Institute
by David Hansel Jan. 4, 2026

Jan. 4, 2026

[image: VVTNS.png] https://www.wwtns.online <https://streaklinks.com/A9c7PbbpKY7PxB6PaAJWGD3-/https%3A%2F%2Fwww.wwtns.on…> - on twitter: wwtns@TheoreticalWide You are cordially invited to the VVTNS 2026 opening lecture Carlos Brody Princeton Neuroscience Institute on the topic of *Towards using large-scale, cross-brain neuronal recordings * *to identify the brain’s internal signals* to identify the brain’s internal signals The lecture will be held on zoom on January 7, 2026, at *11:00 am ET * > To receive the link: https://www.wwtns.online/register-page > *Abstract: *Neural activity is often analyzed with respect to external referents, such as the onset of a sensory stimulus or an overt motor action. Simultaneous recordings allow referencing neurons’ activity to each other and thus detecting signals that are internal to the organism. Further, multi-region simultaneous recordings allow observing how these internal signals are coordinated across the brain. Following this logic in rats performing a perceptual decision-making task, we recorded simultaneously from thousands of neurons across up to 20 brain regions at once. Here we report two internal signals which we found to profoundly shape decision-related neural dynamics and brain states. First, we decoded the continuously evolving decision state separately from each region, and found surprisingly large magnitude co-fluctuations in these measures. Dimensionality analysis showed these to be dominated by a single state variable, suggesting that only a single decision-making computation, not multiple parallel computations, are being carried out during the analyzed period. Second, we found that the precise time the subject commits to a decision – a covert event that we decoded from large-scale neural activity in primary motor cortex – was accompanied by a coordinated change, across the brain, from a decision formation to a post-commitment state. The two states differ substantially in their choice-predictive neural dynamics and in their inter-region correlations. Therefore, knowing the time of this state change on single trials is needed to correctly parse fundamentally different phases of decision-making. Overall, our data suggest that internally-referenced signals and state changes, not timelocked to external events but detectable through simultaneous recordings, are major features of neural activity during cognition. *About VVTNS : Launched as the World Wide Theoretical Neuroscience Seminar (WWTNS) in November 2020 and renamed in homage to Carl van Vreeswijk in Memoriam (April 20, 2022), Speakers have the occasion to talk about theoretical aspects of their work which cannot be discussed in a setting where the majority of the audience consists of experimentalists. The seminars, **held on Wednesdays at 11 am ET,** are 45-50 min long followed by a discussion. The talks are recorded with authorization of the speaker and are available to everybody on our YouTube channel.* ᐧ

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Postdoctoral position in Development and Egocentric Vision.
by Bonnen, Kathryn Jan. 3, 2026

Jan. 3, 2026

Postdoctoral position in Development and Egocentric Vision. The Training Program in Integrative Developmental Processes at Indiana University invites applications for a T32-funded postdoctoral fellowship in Bloomington, Indiana. We seek highly motivated individuals interested in research at the intersection of development, vision science, and computer vision. The postdoctoral fellow will join a collaborative research environment dedicated to understanding developmental processes through egocentric vision in natural tasks, using advanced computational methods and multimodal datasets to advance developmental theory. Indiana University offers a highly interdisciplinary training environment with exceptional career development and mentoring opportunities. The position will be jointly mentored by Dr. Rowan Candy, whose research integrates behavioral, optical, and neuroscientific approaches to study typical and atypical visual development; and Dr. Kathryn Bonnen, a computational neuroscientist specializing in visuomotor coordination in natural tasks. The broader research community includes faculty from Computer Science (Dr. David Crandall, Dr. Zoran Tiganj), Informatics (Dr. Justin Wood, Dr. Samantha Wood), and Psychological and Brain Sciences (Dr. Linda Smith, Dr. Joshua W. Brown, Dr. Ehren Newman). Applicants should have strong computational skills and a background in one or more of the following areas: developmental science, vision science, neuroscience, motor control, computer science, psychology, or related fields. Eligibility: U.S. citizens or permanent residents who currently hold a doctoral degree or will have met all doctoral program requirements before enrolling. Applicants should send a cover letter describing their motivation for applying and a curriculum vitae to: Dr. Rowan Candy (rcandy(a)iu.edu) Dr. Kathryn Bonnen (kbonnen(a)iu.edu) Position is available immediately and will remain open until filled. -- Kathryn Bonnen Assistant Professor, School of Optometry Indiana University kbonnen(a)iu.edu<mailto:kbonnen@iu.edu> https://bonnenlab.github.io

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Review of 2025 in neuroscience
by Mark Humphries (staff) Jan. 2, 2026

Jan. 2, 2026

My regular review of the year in neuroscience is up on The Spike: https://medium.com/the-spike/2025-a-review-of-the-year-in-neuroscience-b062… The tenth of these, would you believe? Enjoy! Mark Professor Mark Humphries | Professor of Computational Neuroscience Office hours: Calendar<https://calendar.google.com/calendar/u/0?cid=a2twY2xkYXNvazVnYnA3ODM2bmFwZ2…> Lab: humphries-lab.org<https://www.humphries-lab.org/> Connect: Bluesky<https://bsky.app/profile/markdhumphries.bsky.social> / LinkedIn<https://www.linkedin.com/in/mark-humphries-65a460212/> / X<https://x.com/markdhumphries> Essays on the brain and science: drmdhumphries.medium.com<https://drmdhumphries.medium.com/> Book: "The Spike: An Epic Journey Through the Brain in 2.1 Seconds" (Princeton UP) in hardback<https://press.princeton.edu/books/hardcover/9780691195889/the-spike?_gl=1*h…..>, paperback<https://press.princeton.edu/books/paperback/9780691241487/the-spike>, ebook<https://press.princeton.edu/books/ebook/9780691213514/the-spike-0?_gl=1*1uf…..> & audiobook<https://press.princeton.edu/books/audio/9780691224091/the-spike?_gl=1*37xz7…..> <https://press.princeton.edu/books/audio/9780691224091/the-spike?_gl=1*37xz7…..> read by Anand Jagatia This message and any attachment are intended solely for the addressee and may contain confidential information. If you have received this message in error, please contact the sender and delete the email and attachment. Any views or opinions expressed by the author of this email do not necessarily reflect the views of the University of Nottingham. Email communications with the University of Nottingham may be monitored where permitted by law.

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The First International Young Scholars Forum,School of AI for Science, Peking University
by Wei Fang Dec. 31, 2025

Dec. 31, 2025

Dear Colleagues: The School of AI for Science, Peking University is planning to host the First International Young Scholars Forum in late January 2026, and will *provide travel grants for outstanding scholars*. This forum is particularly suitable for scholars with interdisciplinary backgrounds in neuroscience and machine learning. In addition, the School of AI for Science, Peking University is actively recruiting outstanding scholars from around the world. *You will have the opportunity to discuss with the school’s faculty and staff the possibility of joining Peking University and obtaining a faculty position during the forum.* Here are the specific details of the forum: -------------------- *The First International Young Scholars Forum* *School of AI for Science, Peking University* *1. **Forum Background* The School of AI for Science at Peking University Shenzhen Graduate School will host the first International Young Scholars Forum in late January 2026. The forum will center on core research areas in the field of AI for Science, with a focus on cutting-edge domains, including the Foundations of AI for Science, AI for Materials Science, AI for Life Sciences, and Computational Mathematics. *2. **School Introduction* In 2025, in response to the scientific revolution and industrial transformation of the intelligent era, with a forward-looking vision, Peking University established the School of AI for Science (the School) at its Shenzhen Graduate School. As the world’s first higher education platform to promote the institutionalized development of AI for Science through an independent academic unit, the School focuses on the deep integration of artificial intelligence and fundamental sciences. It will establish a dual-track mentorship system under the "AI + Science" framework, pioneer a research paradigm that closely integrates scientific principles with big data, and build an open and collaborative innovation ecosystem. By accelerating the process of scientific discovery and shaping the future industrial landscape, the School is committed to cultivating interdisciplinary talents with global perspectives and innovation capabilities. - Student Cultivation: The School has launched the Boya AI for Science (AI4S) Top-Talents Cultivation Program, which selects outstanding undergraduate students from Peking University and Tsinghua University for further studies. It is one of the few schools at the Peking University Shenzhen Graduate School that offers an undergraduate program. Meanwhile, the School is planning and developing the AI4S Teaching Platform. By building a smart, blended teaching platform that integrates online and offline components with laboratory facilities, it aims to provide teachers with a brand-new teaching experience. - Research Support: The School supports the dual-appointment of faculty members in relevant fields at the PengCheng Laboratory, granting them access to the PengCheng Cloud Brain—a world-leading large-scale intelligent computing platform. This provides robust computing power for computing-intensive research projects such as large model development and large scientific facility research, overcoming the computing power bottleneck in scientific research. In addition, the School has taken the lead in establishing the International Alliance of AI for Science, building the AI4S Lab—the world’s first one-stop digital and intelligent life science research platform—and setting up a number of industry-university joint laboratories, while also planning to construct the Guangdong-Hong Kong-Macao Greater Bay Area Institute of AI for Science. Rooted in the innovation hub of the Guangdong-Hong Kong-Macao Greater Bay Area, the School is committed to building a closed-loop, full-chain transformation system integrating basic research, technological breakthroughs, and industrial applications through these initiatives. Collectively, these efforts have forged a comprehensive full-chain platform for faculty to conduct international academic cooperation, facilitate the industrialization of research outcomes, and carry out interdisciplinary research; they enable faculty to connect with top-tier global resources, align with real-world industrial needs, tackle core key technologies in the field of AI for Science, and accelerate the output of cutting-edge research achievements. - Excellent Talents in Collaboration: Through programs such as the National Science Fund for Excellent Young Scholars (overseas), the School has successfully gathered a group of aspiring and accomplished talented young academics. By joining the School, you will collaborate with peers in its open ecosystem, tackle core challenges, and jointly pioneer the future landscape of AI for Science. For more details, please visit the official website of the School of AI for Science at Peking University: https://ai4s.pkusz.edu.cn/en/ *Vision:* Accelerating Scientific Discovery, Defining the Future of Industry *Educational Philosophy:* Rooted in first principles, Driven by intelligence, Promoting interdisciplinarity, Shaping the future. *3. **Registration **Requirements* (1) Ph.D. degree in AI for Science, Artificial Intelligence, fundamental sciences, or a related interdisciplinary field, with a solid academic background. (2) Before April 1, 2026, generally should have obtained formal teaching or research position in an overseas university, scientific research institution, or enterprise R&D institution, and have more than 36 consecutive months of work experience. For those who have obtained a doctorate overseas and have particularly outstanding performance, the working years requirement may be relaxed appropriately. (3) Expertise in specialized fields, rigorous academic integrity, and excellent team spirit. *4. **Registration Method and Required Materials* (1) Application Deadline: 24:00 (Beijing Time), January 15, 2026 (2) Required Materials: Detailed personal resume, title, and abstract of the presentation to be delivered at the forum. (3) Submission Email: ai4s(a)pku.edu.cn Note: The School of AI for Science at Peking University will cover part of the international travel expenses for scholars invited to attend the main forum offline. *5. **Salary and Benefits* Peking University Shenzhen Graduate School is committed to offering a competitive compensation system that meets both domestic and international standards. Our scientific and reasonable salary models have predictable growth mechanisms, and provide comprehensive social security and welfare benefits. Based on the specific position, we offer competitive research start-up funds and dedicated research and office space. We also assist newly recruited faculty apply for various national, Guangdong Provincial, and Shenzhen Municipal talent programs or initiatives. Specific salary and additional benefits are negotiable based on qualifications and experience. *6. **Contact Information* (1) Contact Person: Ms. Bao (2) Email: baojy(a)pku.edu.cn *Welcome to the School of AI for Science at Peking University**—**where innovation meets intelligence!* *Join us, let’s create a new paradigm for scientific research in the era of intelligence together!* -- ----------------------- Wei Fang Postdoc, Electrical & Computer Engineering Yale University, USA

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