Ph3Postdoctoral Research Scientist in NeuroAI /h3 pPosted: /p pJob reference: e6b1d53c5269e e6e f /p pbUniversity of Rome Tor Vergata /b × b@Tether Evo /b /p pThe University of Rome Tor Vergata, in collaboration with b@Tether Evo /b, is looking for a highly motivated bNeuroAI Research Scientist / Machine Learning Engineer /b to join an open, international research effort at the intersection of bartificial intelligence, neuroscience, and brain‑computer interfaces /b. This collaboration brings together academic research and applied AI development to advance our understanding of brain representations and build the next generation of neural interface technologies. The work will focus on bencoding and decoding brain activity /b from invasive and non‑invasive neural recordings, using modern foundation models, representation learning, and generative AI. /p pOur goal is to develop open, reproducible, and high‑impact NeuroAI methods that help explain how the brain represents language, vision, imagery, audition, music, speech, motor control, and semantic structure — while also enabling real‑world progress in BCI systems. /p h3What you’ll work on /h3 ul liMap neural activity into the latent spaces of modern vision, language, and audio foundation models /li liBuild robust encoding and decoding pipelines for fMRI, EEG, MEG, ECoG, iEEG, and related neural data /li liDevelop generative reconstruction systems for images, music, speech, and multimodal brain signals /li liStudy cross‑subject, cross‑modality, and cross‑species alignment of brain representations /li liTest neuroscientific hypotheses about abstraction, compositionality, modality invariance, representational geometry, and shared latent structure /li liContribute to high‑impact publications, open‑source tools, conferences, and international collaborations /li /ul pYou will work in a vibrant research environment connected to Horizon Europe, EIC Pathfinder, national PNRR projects, and collaborations with leading academic and industry partners. /p h3What we’re looking for /h3 ul liA PhD, or near completion, in physics, computer science, engineering, or another quantitative field /li liStrong experience in machine learning, computational neuroscience, neuroimaging, signal processing, or related areas /li liExcellent Python skills and hands‑on experience with deep‑learning frameworks such as PyTorch, JAX, or TensorFlow /li liBackground in one or more of: representation learning, multimodal learning, contrastive learning, diffusion models, LLMs, generative AI, encoding/decoding models, or topographic brain modelling /li liExperience with real neural data such as fMRI, EEG/MEG, ECoG, iEEG, or multi‑unit spiking data /li liStrong scientific communication skills and enthusiasm for interdisciplinary collaboration /li liPublications in top‑tier AI, neuroscience, or computational science venues are highly valued. Open‑source contributions and experience building reproducible research pipelines are also a strong plus. /li /ul h3You will have the opportunity to: /h3 ul liWork on cutting‑edge NeuroAI and BCI research /li liAccess large‑scale neural datasets and state‑of‑the‑art computing resources, including HPC and GPUs /li liCollaborate with international academic labs and industry partners /li liBuild open‑source tools for the scientific community /li liPublish, attend conferences, mentor students, and help define the future of brain‑tech innovation /li liWork in a flexible, international environment /li /ul h3How to apply /h3 pPlease send your bCV /b, a brief bstatement of research interests /b, and optionally b1–2 representative publications, projects, or GitHub links /b to the recruiting contact. Applications are reviewed on a rolling basis. If you are passionate about advancing neuroscience and AI through open, collaborative, and scientifically rigorous research, we would love to hear from you. /p /p #J-18808-Ljbffr