Computational Linguistics Tenure-Track Assistant Professor

We are offering a full time position for 2.5 years within the Transregional Collaborative Research Center (TRR 318) “Constructing Explainability,” which is jointly run by the Universities of Paderborn and Bielefeld. The TRR 318 investigates how algorithmic transparency can be promoted, particularly in the context of black-box models as used in modern artificial intelligence systems. Our subproject aims to capture moments of (non-)understanding of a human interlocutor in their multimodal ensembles and to enable explanatory AI to draw conclusions and adapt its explanatory strategy. Corpus analyses enable the integration of rich, multimodal signals with different perspectives on the degree of understanding of the human interlocutor in different contexts. Beyond computational modeling of monitoring and adaptation in explanations, we evaluate their usefulness for a dynamically adapted conversational agent.

For details about the position, its requirements and how to apply, see here: https://jobs.uni-bielefeld.de/job/view/4932/research-position-m-f-d-in-the-sfb-trr-318-in-the-field-of-multimodal-phonetics?page_lang=en

Full-time | Yerevan, Armenia (On-site / Remote / Relocation Option)

About Saima Inc.
Saima Inc. is a U.S.-based deep-tech Voice AI company developing Hecttor (www.hecttor.ai), a real-time voice intelligence platform that makes human and AI voice communication clearer, more intelligible, and more reliable.
Hecttor develops proprietary technologies across speech enhancement, noise cancellation, bandwidth extension, speech reconstruction, and real-time audio processing, serving use cases across contact centers, Voice AI, telecommunications, and mission-critical communications. Saima holds three granted U.S. patents, with its core AI research and engineering team based
in Yerevan, Armenia.

Role Overview
We are looking for a Senior AI Researcher specializing in speech and audio processing to lead research and help advance our audio AI technologies.
This is a research-focused role for someone with deep experience in machine learning, speech and audio processing, and signal processing.
You will help define research priorities, run experiments, evaluate new methods, and stay closely connected to the latest developments in academia and industry. You will also work with engineering teams to bring successful research into real products.

Key Responsibilities
● Lead research projects in speech, audio, and machine learning.
● Explore and develop new approaches for improving speech and audio models.
● Define research directions and identify promising areas for innovation.
● Collaborate with AI engineers to move successful research into production.
● Share knowledge and support the technical growth of the team.

Ideal Background
● Extensive experience in speech processing, audio AI, machine learning, signal processing, or related fields.
● Deep understanding of machine learning for speech and audio.
● Proven experience leading research projects and developing new ideas.
● Strong understanding of acoustics, signal processing, and real-world audio problems.
● A strong publication record in relevant research areas is highly valued.
● PhD or equivalent research experience in a relevant field is highly valued.

Contacts:
Mat, CEO - mat@hecttor.ai, +37499111623 (whatsapp)
Narek, CTO - narek@hecttor.ai +37477877466 (whatsapp)

Full-time | Yerevan, Armenia (On-site / Remote / Relocation Option)

About Saima Inc.
Saima Inc. is a U.S.-based deep-tech Voice AI company developing Hecttor (www.hecttor.ai), a real-time voice intelligence platform that makes human and AI voice communication clearer, more intelligible, and more reliable.
Hecttor develops proprietary technologies across speech enhancement, noise cancellation, bandwidth extension, speech reconstruction, and real-time audio processing, serving use cases across contact centers, Voice AI, telecommunications, and mission-critical communications. Saima holds three granted U.S. patents, with its core AI research and engineering team based
in Yerevan, Armenia.

Role Overview
We are looking for a Senior AI Engineer specializing in speech and audio to bring machine learning models from research into production and real-world devices. This role is focused on model deployment, optimization, evaluation, and production performance. You will work on making AI models fast, efficient, reliable, and ready to run across different platforms and hardware environments. You will also work closely with researchers and product engineering teams to turn research models into production systems while balancing model quality, latency, compute, memory usage, and power consumption.

Key Responsibilities
● Bring speech and audio AI models from research into production.
● Optimize models for real-time performance across different devices and platforms.
● Build and improve model evaluation and benchmarking processes.
● Work with researchers to adapt models for production and device constraints.
● Help define best practices for production AI engineering.

Ideal Background
● Strong experience with Python and C/C++, and modern ML frameworks such as PyTorch.
● Extensive experience building and deploying machine learning systems in production.
● Strong experience with model optimization, inference, and performance improvement.
● Experience working with real-time, mobile, embedded, or edge systems.
● Experience with model evaluation and benchmarking.
● Experience with speech, audio, signal processing, or other real-time AI applications is highly
valued.

Contacts:
Mat, CEO - mat@hecttor.ai, +37499111623 (whatsapp)
Narek, CTO - narek@hecttor.ai +37477877466 (whatsapp)

We are recruiting a fully funded, three-year PhD candidate for a project on Privacy-Preserving Speech Understanding with Multimodal Signals for Clinical Applications, hosted by the MULTISPEECH team at LORIA (Université de Lorraine, Inria and CNRS), in Villers-lès-Nancy, France.

The project is funded by the AI Grand Est ENACT research chair and will investigate methods to protect speaker identity and sensitive content while preserving the semantic and diagnostic information needed for clinical speech understanding. The work will combine speech and text, with the possibility of incorporating an additional modality such as physiological signals, medical imaging or electronic health-record metadata. It will involve privacy-preserving speech processing, speech/audio foundation models, multimodal machine learning, and evaluation of privacy–utility trade-offs.

We welcome candidates with a Master’s or engineering degree in computer science, AI, signal or speech processing, applied mathematics, data science, or a related area. Strong Python and machine-learning/deep-learning skills are expected. Experience in speech processing, NLP, privacy-preserving ML, multimodal learning, or AI for healthcare is particularly welcome.

• Location: Villers-lès-Nancy, France
• Duration: 3 years, 1 October 2026 to 30 September 2029
• Start date: 1 October 2026 (or 1 November 2026)
  
• Salary: €2,300 gross per month
• Application deadline: Applications reviewed until the position is filled; final deadline 30 August 2026, potentially extended to 20 September 2026

Applicants should email a CV, motivation letter, degree transcripts, and, if available, two recommendation letters or the contact details of two referees.

For the full position description and application details, please see: https://sites.google.com/view/natalia-tomashenko/recruitment-phd-positions Contact: Natalia Tomashenko, natalia.tomashenko@inria.fr

Job at Auphonic: Audio Machine/Deep Learning & Signal Processing
Engineer (Graz/Austria)

Hallo!

Auphonic is looking for a Machine/Deep Learning & Signal Processing
Engineer in Graz, Austria:

"Work on real-world audio AI — from classic DSP to large deep learning
models — using our large-scale datasets and GPU infrastructure."

More details: https://auphonic.com/jobs/ml-engineer

LG
Georg

The Speech and Multimodal Intelligent Information Processing (SMIIP) Lab at the Chinese University of Hong Kong, Shenzhen has multiple open positions for fully funded Ph.D. student and Postdoc Researchers (2 years contract).

Our research interests lie in the areas of intelligent speech processing, embodied audition and dialogue system as well as multimodal behavior signal analysis and interpretation.

Email: mingli369@cuhk.edu.cn

PI information: Prof. Ming Li https://sai.cuhk.edu.cn/en/teacher/258

Lab Website: https://smiip-mli.github.io/

PhD admission information: https://sai.cuhk.edu.cn/en/node/35

Postdoc recruitment information: https://www.cuhk.edu.cn/en/taxonomy/term/50

It is highly recommended to contact Prof. Ming Li through email before the application. Thanks.

We’re looking for a strong product leader who can drive roadmap, prioritization, and product direction — and who’s excited by the intersection of language, community, and AI. This role will help lead Common Voice, Mozilla’s global, community-powered platform helping make AI more inclusive by ensuring speakers of the world’s languages can be represented in training data.

We’d especially love to hear from people with:

• strong senior product leadership experience
• sound judgement and comfort making tradeoffs across roadmap, platform health, and community needs
• experience working across engineers, data scientists, designers, linguists, language activists, and other collaborators
• knowledge of linguistics or languages
• a basic grounding in computational linguistics or NLP

Nice to have experience:

• ML/AI product experience or academic training in ML/AI
• knowledge of voice or speech AI
• multilingual or language-centered experience

Follow this link to apply: https://job-boards.greenhouse.io/mozilla/jobs/7813301 

At the MSAD groupe, within the LIST3N laboratory at the University of Technologi of Troyes, we are offering a research internship.

The aim of this internship is to explore and analyze a new approach based on collaborative knowledge distillation where teacher and student are trained simultaneously.

Each model mutually enriches the other through a reciprocal influence on their learning processes, going beyond traditional unidirectional transfer.

To validate this concept, the approach will be applied to speech recognition based on Connectionist Temporal Classification (CTC).

A known problem with CTC is alignment divergence: models trained separately on the same data often develop inconsistent temporal alignments.

With collaborative learning, we hypothesize that they will naturally converge towards a unified alignment, thus improving robustness and performance.

Main Tasks

• State of the Art : Analyze current research on Collaborative Knowledge Distillation (CKD), with a specific focus on its application to CTC-based speech recognition.
• Knowledge aggregation: Determine how to efficiently merge knowledge from multiple networks.
• Learning stabilization: Design regularization mechanisms to ensure a stable and balanced training process.
• Robustness assessment: Test the performance of the models under various conditions to validate their reliability.

Candidate's profile

• Education Level: Master's student (2nd year of research)
• Skills: Strong background in machine learning and deep learning.
• Development Requirements : Python proficiency and PyTorch experience.
• Preferred Assets: Interest in or experience with deep learning, Transformer architecture, speech recognition, and knowledge distillation.

Intership modalities

• Internship Start Date : September/October 2026 (depending on student’s availability)
• Internship Duration : 6 months
• Location : Université de Technologie de Troyes (UTT), France
• Language : English or French
• Expected Internship Level: M1 or M2
• Gross remuneration : 600€/month

Application

If you wish to be considered for this internship opportunity, please send your CV and cover letter to mohammed_faouzi.benzeghiba@utt.fr

The University of Oldenburg, Germany, is seeking to fill a permanent
professorship (salary scale W2) of Medical Physics with focus on
Technical and Experimental Audiology. For more information about the
position, please visit https://uol.de/en/job/medical-physics-tea-1027.
The professorship is part of the Department of Medical Physics and
Acoustics (https://uol.de/en/mediphysics-acoustics). Please contact
Prof. Dr. Volker Hohmann (Email: volker.hohmann@uni-oldenburg.de) if you
have any questions.