Bala Cynwyd (Philadelphia Area), Pennsylvania United States

Overview At Susquehanna, we approach quantitative finance with a deep commitment to scientific rigor and innovation. Our research leverages vast and diverse datasets, applying cutting-edge machine learning at scale to uncover actionable insights—driving data-informed decisions from predictive modeling to strategic execution.

We are launching a 12–18 month fully funded faculty fellowship. This is a unique opportunity to pursue advanced machine learning research in a fast-paced, real-world environment—collaborating with teams at the frontier of quantitative trading.

What You'll Do

 • Conduct applied machine learning research using large-scale, real-world financial datasets

 • Develop novel modeling techniques and adapt state-of-the-art algorithms to unique challenges in quantitative finance

 • Collaborate with researchers and engineers to translate theoretical insights into production-scale systems.

 • Contribute to the design of robust, high-performance ML infrastructure

 • Explore research directions aligned with your interests, with flexibility in scope and duration

 • Evaluate ideas in an industrial setting, generating insights that may inform future academic or applied work

 • Help grow our research community by fostering collaboration and leveraging your network within the ML and academic ecosystems

What we're looking for • Exceptional faculty (tenured or tenure-track) with expertise in machine learning, deep learning, LLM, statistics, computer science, physics, applied mathematics, or related fields

 • Exceptional newly minted PhDs or postdocs developing a research agenda in machine learning, deep learning, LLM,  statistics, computer science, physics, applied mathematics, or related fields

 • A strong theoretical foundation in ML and a passion for solving practical, open-ended problems

 • Strong programming skills (Python preferred); experience with ML frameworks like PyTorch, TensorFlow or Jax

 • Intellectual curiosity, adaptability, and a collaborative mindset

Note: This fellowship is ideal for faculty seeking to broaden their applied research portfolio, explore new domains, or engage in sabbatical collaborations. The faculty fellowship is also appropriate for exceptional newly minted PhD and postdocs who want to develop a research agenda (involving, but not limited to, modeling, inference, and prediction tasks in complex systems), as they prepare to transition into a faculty position. While research outputs cannot be published due to the proprietary nature of our work, we aim for each faculty fellow to publish technical research papers collaboratively with their research hosts, to showcase some of the machine learning and AI innovations that they developed while in residence at Susquehanna.

About AIMATX

AIMATX is a Berkeley-based startup revolutionizing materials science by creating next-generation materials and molecules that power the future economy. Our AI-driven platform explores vast chemical spaces, predicts new materials and their properties, and accelerates discovery through intelligent, targeted experimentation. By reducing years of R&D to weeks, we are shaping the future of materials innovation;come join us!

AIMATX is built and guided by a world-class team at the intersection of science, AI and engineering. Our leadership includes Omar Yaghi (2025 Nobel Prize), Fernando Perez inventor of Jupyter/IPython, alongside former CEOs of public companies and leading researchers in generative AI and autonomous experimentation. This ecosystem brings unmatched scientific depth, computational expertise, and entrepreneurial excellence to accelerate the future of discovery.

Role Overview

We are seeking a highly skilled Computational Chemist / Materials Scientist to join our innovative team. You will apply your expertise in chemical and materials science R&D to develop sustainable, high-performance materials tailored to specific use cases. As part of our technical team, you will:

• Develop and apply AI-computational tools to predict novel material structures and properties.
• Design and implement machine learning algorithms to analyze large datasets and predict material behavior.
• Build AI-based methods for synthesis prediction of candidate materials.
• Collaborate with engineering teams to translate computational predictions into high-throughput experimental workflows.
• Incorporate experimental feedback into predictive models to improve accuracy within a closed-loop, self-improving platform.
• Analyze and visualize theoretical and experimental data, presenting insights to stakeholders and guiding research and product strategy.
• Work with data science experts to quantify and calibrate uncertainties across the predictive pipeline.
• Stay current with scientific advances and integrate relevant ideas into ongoing projects.
• Implement computational methods in a rigorously tested codebase deployed using modern software engineering best practices.

Required Qualifications

• PhD in Machine Learning, Computational Chemistry, Chemistry, Materials Science, Physics or a related field.
• Experience applying machine learning to scientific or structured data
• Proficiency with Python, GitHub workflows, testing, documentation, and continuous integration.
• Demonstrated leadership and project ownership in computational or ML-driven research.

Preferred Qualifications

• Experience developing modeling approaches, including physics-based atomistic modeling.
• Experience in polymer chemistry, ceramics, nanomaterials, or related areas.
• Publication record in peer-reviewed journals and presentations at scientific conferences.

Soft Skills & Cultural Fit

• Excellent written and verbal communication skills.
• Collaborative mindset and ability to work effectively in a multidisciplinary team.
• Strong organization, attention to detail, and a results-driven attitude.
• Proactive and self-motivated, with the ability to take initiative.
• Commitment to scientific rigor, innovation, and continuous learning.

Benefits & Perks

We offer a competitive salary with bonus potential and meaningful early equity. Compensation reflects experience, expertise and expected impact.

Additional benefits may include: - Flexible work arrangements and remote options. - Medical, dental, and vision coverage. - 401(k) with company matching. - Generous PTO and parental leave.

Equal Opportunity Statement

AIMATX is committed to fostering a diverse and inclusive workplace. All qualified applicants will receive consideration without regard to race, color, religion, gender, sexual orientation, gender identity, national origin, disability, or vet

Send your CV to theo.jaf@aimatx.ai

Postdoctoral Scholar: Computational Medicine Research Group, University of California, Irvine (NIH Funded)

The Computational Medicine Research Group directed by Prof. Pratik Shah at the University of California, Irvine, invites applications for an NIH-funded Postdoctoral Scholar position. We seek outstanding Ph.D. candidates in computer science, biomedical informatics, statistics, or related fields to develop novel deep learning and AI technologies for digital biopsies from medical images and clinical decision-making from non-imaging datasets. Research areas include:

• Generative AI for Medical Imaging & Digital Biopsies: Developing and interpreting DNNs for automated tissue analyses using high-parameter images (pathology, MRI, CT, RGB) and validating these models in collaboration with hospitals nationwide.

• Generative & Predictive AI for Clinical Decision Support: Developing biologically informed statistical methods and uncertainty estimation generative models for explainable clinical decision-making from EMRs and genetic data.

Responsibilities include data preprocessing, training and real-world validation of generative deep learning models (GANs, Diffusion models, Transformers), developing novel statistical models, and publishing research in leading journals and conferences. Comprehensive training in publication, fellowship and grant writing, and career development for roles in academia, industry, or government will be provided.More information about the lab can be found at https://faculty.sites.uci.edu/pratikshahlab/

Rochester, Minnesota, USA

Mayo Clinic seeks a highly motivated individual to advance the development, validation, and real-world implementation of generative AI systems for clinical decision support in Gastroenterology and Hepatology. This role bridges research and translation into clinical workflows, focusing on building trustworthy AI systems that augment human presence and put the needs of the patient first. Research Fellows will work within a multidisciplinary team of data scientists, physicians, and engineers to design novel generative agentic architectures, develop useful benchmarks, and work together with clinical teams to decrease time to diagnosis and time to treatment. Contact shung.dennis@mayo.edu if interested.

Open positions in Mathematical, Statistical and Computational aspects of Artificial Intelligence and Machine Learning.

The Faculty of Mathematics and the Institute for Mathematical and Computational Engineering (IMC) from the Pontificia Universidad Católica de Chile (UC) are offering up to two full-time professor positions at the assistant or associate level. The successful candidate will have a joint appointment between the Faculty of Mathematics and the IMC. We welcome applications from highly qualified candidates with a track record of excellent research and a solid commitment to excellence in teaching and supervision. This position is intended for those researchers interested in advancing the mathematical, statistical and computational aspects of modern artificial intelligence, machine learning and its applications. Candidates conducting research in areas including pure and computational mathematics, mathematical modeling, statistics, optimization, and theoretical computer science, that exhibit a convincing path towards AI research are also encouraged to apply.

The successful candidate will contribute to teaching courses at the Institute for Mathematical and Computational Engineering and the Faculty of Mathematics. The typical teaching load is three semester-long courses a year, at the graduate or undergraduate level, split between the two academic units. Command of Spanish is not required for applying; however, the selected candidate is expected to start teaching in Spanish in at most two years. Applicants who do not speak Spanish will receive support from the University to learn the language adequately. To support the initial academic career stages, the incorporation of Assistant Professors can benefit from an initial reduction of the teaching load and a starting fund. The applicant position and salary will be adjusted, according to the policies and regulations at UC, on the applicant starting date. These will be determined according to the previous experience of the candidate. UC is committed to the values of diversity regarding origin, gender, and ethnicity to build a more diverse and inclusive community. For the current call, women are especially encouraged to apply.

APPLICATIONS

Applications are received through MATHJOBS platform at the link https://www.mathjobs.org/jobs/list/27675 or can be sent by email at vacancysearch.imc@uc.cl. The documentation submitted must include at least:

• Cover letter.
• Curriculum vitae.
• Publication list.
• Research statement.
• Teaching statement.
• Three (3) letters of recommendation, with ideally at least one of them referring to the teaching experience.

The deadline for the applications is December 16th, 2025. Queries can be made by email to Prof. Cristóbal Rojas at vacancysearch.imc@uc.cl.

VISA

If selected for a position, a foreigner without permanent residency in Chile or applying from abroad will need to request a visa in the consulate of their country of origin to be incorporated as academic staff at UC Chile.

Further information about IMC and the Faculty of Mathematics can be found at https://imc.uc.cl and www.mat.uc.cl.

Pinely is a privately owned algorithmic trading firm specializing in high-frequency and mid-frequency trading. We’re based in Amsterdam, Cyprus, and Singapore, and we’re experiencing rapid growth. We are looking for a DL Research Group Lead to drive cutting-edge AI research and lead a core DL subgroup. As DL becomes a central engine of the business, your team’s impact will grow across major markets and asset classes.

Responsibilities:

• Lead development of AI models, especially foundational models for market data, to predict prices in noisy, fast-changing markets;
• Set the research agenda, design experiments, and validate results;
• Build and manage a high-performing research team;
• Ensure a fast, transparent, value-driven research process;
• Integrate contributions from multiple researchers into production-ready solutions;
• Contribute hands-on to coding and strategy development;
• Expand responsibilities within the DL department over time.

Requirements:

• Strong DL researcher with technical leadership experience;
• Preferably experienced in high-end AI domains (LLMs, reasoning, generative models);
• Motivated by deep research and real-world impact;
• Able to maintain high pace while supporting a healthy team culture;
• Trading experience optional — first-principles thinking is key.

What we offer:

• Relocation package to Amsterdam
• High impact on a core business function and direct influence on real PnL;
• Minimal bureaucracy, fast feedback loops, massive datasets, reproducible experiments;
• Strong engineering support and an H200-based Data Center growing 2× yearly;
• Work on extremely challenging, non-stationary markets with low signal-to-noise;
• Opportunity to build foundational models for finance and shape the future of quant AI;
• Freedom to pursue deep research and define your modeling vision;
• A top-tier team, on-site in Amsterdam, working directly with founders;
• Influence over team hiring and development.
• Internal training, comprehensive health insurance, sports reimbursement, and biannual corporate events

Shanghai

Key Responsibilities • Building the compute platform and machine learning libraries for large scale machine learning and simulation workloads • Focus on compute platform stability and efficiency on both CPU and GPU clusters, making the platform observable and scalable • Utilize cluster monitoring and profiling tools to identify bottlenecks and optimize both infrastructure and software system • Troubleshoot and resolve issues related to OS, storage, network, and GPUs

Challenges You Will Tackle: design, build and improve our compute platform for PB scale data model training and simulations with a wide range of machine learning models by leveraging our existing research infrastructure.

Requirements: • Solid experience in running production machine learning infrastructure at a large scale • Experience in designing, deploying, profiling and troubleshooting in Linux-based computing environments • Proficiency in containerization, parallel computing and distributed training algorithms • Experience with storage solutions for large scale, cluster-based data intensive workloads

Bonus qualification: • Experience of supporting machine learning researchers or data scientists for production workloads

WHAT YOU CAN EXPECT FROM US: In return for you joining our elite team, you will be offered a competitive salary package as well as access to a plethora of Optiver-perks. To hear more about what it is like to work here and our great culture, apply now and take the first step towards the best career move you will ever make!

DIVERSITY AND INCLUSION Optiver is committed to diversity and inclusion, and it is hardwired through every stage of our hiring process. We encourage applications from candidates from any and all backgrounds, and we welcome requests for reasonable adjustments during the process to ensure that you can best demonstrate your abilities.

PRIVACY DISCLAIMER

Optiver 重视个人信息的保护。请您在提供个人信息给我们之前，认真阅读Optiver China Privacy Notice, 了解我们如何收集及处理您的个人信息。 Personal information protection is of utmost importance to Optiver. Before you provide any personal information to us, we strongly urge you to read our Privacy Policy to acknowledge how we collect and process your personal information.

Remote - Americas

Applied Machine Learning Engineer - Search

Every day, millions of people search for products across Shopify's ecosystem. That's not just queries—that's dreams, businesses, and livelihoods riding on whether someone finds the perfect vintage jacket or the exact drill bit they need. As a Machine Learning Engineer specializing in Search Recommendations, you'll be the one making that magic happen. With a search index unifying over a billion products, you're tackling one of the hardest search problems at unprecedented scale. We're building cutting-edge product search from the ground up using the latest LLM advances and vector matching technologies to create search experiences that truly understand what people are looking for.

Key Responsibilities:

• Design and implement AI-powered features to enhance search recommendations and personalization
• Collaborate with data scientists and engineers to productionize data products through rigorous experimentation and metrics analysis
• Build and maintain robust, scalable data pipelines for search and recommendation systems
• Develop comprehensive tools for evaluation and relevance engineering, following high-quality software engineering practices
• Mentor engineers and data scientists while fostering a culture of innovation and technical excellence

Qualifications:

• Expertise in relevance engineering and recommendation systems, with hands-on experience in Elasticsearch, Solr, or vector databases
• Strong proficiency in Python with solid object-oriented programming skills
• Proven ability to write optimized, low-latency code for high-performance systems
• Experience deploying machine learning, NLP, or generative AI products at scale (strong plus)
• Familiarity with statistical methods and exposure to Ruby, Rails, or Rust (advantageous)
• Track record of shipping ML solutions that real users depend on

This role may require on-call work

Ready to connect merchants with their perfect customers? Join the team that's making commerce better for everyone.


At Shopify, we pride ourselves on moving quickly—not just in shipping, but in our hiring process as well. If you're ready to apply, please be prepared to interview with us within the week. Our goal is to complete the entire interview loop within 30 days. You will be expected to complete a live pair programming session, come prepared with your own IDE.


About the multiple postdoctoral fellowship positions: Join the Deep Learning for Precision Health Lab at the University of Texas Southwestern to build next-generation AI for medicine with direct access to large, deeply-phenotyped datasets and clinical partners across UT Southwestern Medical Center, Children’s Medical Center, and Parkland Hospital. Roles are ideal for researchers who have recently (or will soon) completed a PhD (typically ≤3 years from degree). Based in Dallas—one of the largest, most vibrant, and fastest-growing cities in the U.S. —fellows work closely with Prof. Albert Montillo, PhD (Associate Professor, tenured, Fellow of IEEE/ MICCAI / ISMRM / OHBM / SPIE/ ASNR) and collaborate with neurologists, radiologists, psychiatrists, and neuroscientists on clinically grounded problems—aimed at high-impact publications and deployable methods.

Project tracks (pick one or blend across): 1. Deep multimodal fusion models & GNNs: Integrate multi-contrast MRI & PET with electrophysiology, EHR/clinical data, and multi-omics via deep fusion and graph learning to predict disease trajectories and treatment response (Opportunities in Parkinson’s, AD, ASD, epilepsy, depression). 2. Image foundation models (FMs): Pretrain & fine-tune on very large medical image datasets (10k–100k+ subjects) for site-generalizable transfer to downstream tasks with per-subject explainability. 3. Bayesian Causal Discovery method development: Combine neuroimaging, interventional data, and priors to infer effective brain connectivity and mechanisms in developmental disorders (epilepsy, ASD).
4. Reinforcement learning to guide neuromodulation therapy: Fuse computational neuroscience models with data-driven FMs, optimizing neuromodulation under uncertainty. 5. Speech + Imaging for early dementia: Build multimodal FMs over voice (audio), language (linguistics/NLP), and neuroimaging for earliest, most accurate dementia diagnosis.

Required Qualifications:

1. We will only consider scholars having (or will have) PhD degrees in CS, ECE, Applied Math, Computational Physics, BME, Bioinformatics, Statistics, or related field with machine learning and signal/audio/text or omics analysis experience (e.g., MRI/CT/PET; MEG/EEG; speech/voice; NLP/clinical text; genomics/proteomics).
2. Proficient in DL programming in Python (PyTorch/TensorFlow) and strong mathematical training for fast DL prototyping.
3. Major contributions in peer-reviewed publications at top venues: NeurIPS/ICLR/ICML/AAAI, MICCAI, CVPR/ICCV, journals such as TPAMI, TMI, MedIA, Nature Communications, and related high-impact outlets.

Appointment and support:

Full-time position with competitive salary & benefits, based in Dallas, TX, USA. Initial appointment is 1 year, renewable; fellows should plan for minimum 2-yr commitment. US citizens strongly encouraged; visa sponsorship for exceptional international candidates. Start window: early 2026; later starts considered.

For consideration:

Reach out for an in-person meeting in San Diego at NeurIPS 2025 (or virtually afterwards) via email to Albert.Montillo@UTSouthwestern.edu with the subject “Postdoc-Applicant-MM/FM-NeurIPS” and include: (1) CV, (2) contact info for 3 references, (3) up to 3 representative publications, and (4) your preferred track(s) + start window. Positions open until filled; review begins immediately.

New York

As a Data Scientist, you will analyze complex datasets, build predictive models, and generate insights that drive strategic decisions. You’ll partner with engineers, researchers, and business leaders to turn data into actionable outcomes. Opportunities may be available from time to time in any location in which the business is based for suitable candidates. If you are interested in a career with Citadel, please share your details and we will contact you if there is a vacancy available.