md senior research scientist

Amazon.com

<div><h2 class="jobSectionHeader"><b>DESCRIPTION</b></h2><div>
Amazon&rsquo;s global talent is incredibly complex with unique problems to be solved for each line of business. Global Talent Management (GTM) is centrally responsible for managing and evolving Amazon&rsquo;s human capital through intelligent talent products and processes. GTM Science is a growing interdisciplinary science team within GTM that develops science products and services to facilitate Amazon&rsquo;s growth and development of talent across all of our businesses and locations around the world.
<br>
<br>
Our vision in GTM Science is to use machine learning and science to scalably solve organizational challenges focused on talent movement, talent differentiation, employee-role matching, promotion processes, organizational design and succession planning, diversity and inclusion, and new areas that address the evolving needs of our diverse employee base.
<br>
<br>
We are looking for an experienced machine learning scientist to work on talent science products that draw from a range of fields such as algorithmic fairness, natural language processing, supervised and unsupervised learning, recommendation systems, machine learning on graphs, reinforcement learning and others on rich and novel datasets. The role has high visibility to senior Amazon business leaders and involves working with other scientists, and partnering with engineering and product teams to integrate these models into production systems.
<br>
<br>
As an applied scientist in GTM Science, you will have the opportunity to work on exciting problems in one of the most innovative applications of science in the People Experience and Technology space. You will help to solve high impact business problems in an unconventional domain, and be encouraged to patent and publish your contributions. If this kind of work excites you, reach out to us to find out more!
<br>
<br>
Key Responsibilities
<br>
<ul><li>Design and implement models, science-based product ideas and features, project plans and communicate with stakeholders.
</li><li>Develop fair predictive models to understand important business and people-centered outcomes
</li><li>Productionize ML and science models at the scale of Amazon
</li></ul></div><h2 class="jobSectionHeader"><b>BASIC QUALIFICATIONS</b></h2><ul><li>3+ years of building machine learning models for business application experience</li><li>PhD, or Master's degree and 6+ years of applied research experience</li><li>Experience programming in Java, C++, Python or related language</li><li>Experience with neural deep learning methods and machine learning</li></ul><h2 class="jobSectionHeader"><b>
PREFERRED QUALIFICATIONS</b></h2><ul><li>Experience with modeling tools such as R, scikit-learn, Spark MLLib, MxNet, Tensorflow, numpy, scipy etc.</li><li>Experience with large scale distributed systems such as Hadoop, Spark etc.</li></ul><br>
Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status.<br>
<br>
Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you&rsquo;re applying in isn&rsquo;t listed, please contact your Recruiting Partner.<br>
<br>
Our compensation reflects the cost of labor across several US geographic markets. The base pay for this position ranges from $150,400/year in our lowest geographic market up to $260,000/year in our highest geographic market. Pay is based on a number of factors including market location and may vary depending on job-related knowledge, skills, and experience. Amazon is a total compensation company. Dependent on the position offered, equity, sign-on payments, and other forms of compensation may be provided as part of a total compensation package, in addition to a full range of medical, financial, and/or other benefits. For more information, please visit https://www.aboutamazon.com/workplace/employee-benefits. This position will remain posted until filled. Applicants should apply via our internal or external career site.</div>

Sr. Applied Scientist , AMX Science

Argonne National Laboratory

<div><div>Argonne National Laboratory seeks a Postdoctoral Appointee to perform computational research on materials for thermal and electrochemical interfaces. The successful candidate will integrate first-principles and atomistic simulations with machine-learned interatomic potentials to:</div><div></div><ul><li>
Model reaction pathways on metal-oxide surface, including adsorption, reactions and diffusion steps.</li><li>
Construct atomistic structural models and compute electronic and vibrational properties.</li><li>
Develop and train neural-network or other machine-learned interatomic potentials to enable large-scale molecular dynamics (MD) simulations with near-DFT fidelity.</li><li>
Perform MD simulations to quantify thermal transport across interfaces and evaluate phonon coupling/phonon scattering mechanisms.</li><li>
Derive design rules relating synthesis to thermal and chemical properties; provide computational guidance to experimental synthesis.</li><li>
Collaborate closely with experimental teams to validate and refine models.</li><li>
Publish results in high-impact journals, present at conferences, and contribute to data sets and code repositories.</li></ul><div></div><div>
Position Requirements</div><div></div><div>
Required Skills, Knowledge and Experience:</div><ul><li>
Ph.D. (received within the last 0&ndash;5 years or by start date) in Physics, Materials Science, Chemistry, Chemical Engineering, Applied Physics, or a closely related field with a focus on computational materials modeling.</li><li>
Density Functional Theory (DFT) for surfaces and interfaces; experience computing reaction energies/barriers (e.g., NEB).</li><li>
Proficiency with one or more DFT packages (e.g., VASP) and phonon tools (e.g., Phonopy).</li><li>
Classical/ab initio Molecular Dynamics (MD) simulations of thermal transport; familiarity with NEMD and/or Green&ndash;Kubo approaches using LAMMPS or similar.</li><li>
Experience developing and applying machine-learned interatomic potentials and validating them against DFT.</li><li>
Atomistic modeling of reactions on metal oxides, including electrochemical reactions.</li><li>
Understanding of interfacial thermal transport, thermal boundary conductance, and phonon coupling across interfaces.</li><li>
Programming and HPC:</li><li>
Strong scripting and data analysis skills; experience with high-performance computing environments and job schedulers.</li><li>
Demonstrated ability to work in multidisciplinary teams and to communicate complex results effectively in writing and presentations.</li><li>
Record of peer-reviewed publications commensurate with career stage.</li><li>
Commitment to Argonne&rsquo;s core values and safe work practices; ability to pass a DOE background check per lab requirements.</li></ul><div></div><div>
Preferred Skills, but Not Required:</div><ul><li>
Background in integration of computational results with experimental data.</li><li>
Experience with workflow automation and reproducible research practices.</li><li>
Experience with machine learning in computational materials.</li></ul><div></div><div>
Please upload the following as attachments to your application via Workday:</div><ul><li>
CV/Resume</li><li>
Unofficial Ph.D. Transcripts</li><li>
If already awarded, a copy of your Ph.D. diploma. Candidates can be currently enrolled to apply, but must have proof of degree conferral by the position start date.</li></ul><div></div><div>
At the point of interview, candidates will be asked to submit the name/contact of three references.</div><div></div><div>
Job Family</div>
Postdoctoral<div></div><div>
Job Profile</div>
Postdoctoral Appointee<div></div><div>
Worker Type</div>
Long-Term (Fixed Term)<div></div><div>
Time Type</div>
Full time<div></div>
The expected hiring range for this position is $70,758.00-$117,925.00.<div></div><div>
Please note that the pay range information is a general guideline only. The pay offered to a selected candidate will be determined based on factors such as, but not limited to, the scope and responsibilities of the position, the qualifications of the selected candidate, business considerations, internal equity, and external market pay for comparable jobs. Additionally, comprehensive benefits are part of the total rewards package.</div><div></div><div>
Click <div>here</div> to view Argonne employee benefits!</div><div></div><div><i>
As an equal employment opportunity employer, and in accordance with our core values of impact, safety, respect, integrity and teamwork, Argonne National Laboratory is committed to a safe and welcoming workplace that fosters collaborative scientific discovery and innovation. Argonne encourages everyone to apply for employment. Argonne is committed to nondiscrimination and considers all qualified applicants for employment without regard to any characteristic protected by law.</i></div><div></div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><i>
Argonne employees, and certain guest researchers and contractors, are subject to particular restrictions related to participation in Foreign Government Sponsored or Affiliated Activities, as defined and detailed in United States Department of Energy Order 486.1A. You will be asked to disclose any such participation in the application phase for review by Argonne's Legal Department.</i></div><div></div><div><i>
All Argonne offers of employment are contingent upon a background check that includes an assessment of criminal conviction history conducted on an individualized and case-by-case basis. Please be advised that Argonne positions require upon hire (or may require in the future) for the individual be to obtain a government access authorization that involves additional background check requirements. Failure to obtain or maintain such government access authorization could result in the withdrawal of a job offer or future termination of employment.</i></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div>

Postdoctoral Appointee - MSD Computational Materials

Visa

<div><b>Company Description</b><p><br>
Visa is a world leader in payments and technology, with over 259 billion payments transactions flowing safely between consumers, merchants, financial institutions, and government entities in more than 200 countries and territories each year. Our mission is to connect the world through the most innovative, convenient, reliable, and secure payments network, enabling individuals, businesses, and economies to thrive while driven by a common purpose &ndash; to uplift everyone, everywhere by being the best way to pay and be paid.</p><p>
Make an impact with a purpose-driven industry leader. Join us today and experience Life at Visa.</p><b><br>
Job Description</b><p><br>
We are looking for a Staff ML Scientist to design and develop next&#8209;generation AI and ML models that solve real&#8209;world challenges in the payments ecosystem covering transaction monitoring, fraud detection, and risk mitigation across multiple Visa businesses. You will be part of cross-functional team of data scientists and ML engineers based out of Bangalore and collaborating globally, driving innovation in the Risk and Identity Solutions (RaIS) through advanced AI/ML technologies.</p><p>
You will combine deep technical expertise with ownership, velocity, and influence. You will drive the scientific roadmap at scale, ensuring models are aligned, explainable, and robust, and you&rsquo;ll collaborate with world&#8209;class experts while influencing product strategy in a high&#8209;stakes domain. The position offers access to top&#8209;tier compute, tools, and datasets, and a collaborative, innovative culture focused on shaping the future of global payments.</p><p>
Responsibilities</p><ul><li>
Extract insights from large-scale Visa datasets across business lines to define high-value, fit-for-purpose problems beyond payments - driving clarity and framing business impact with precision.</li><li>
Rapidly design, experiment, and deploy SOTA ML/AI models, owning the full lifecycle and ensuring solutions are scalable, measurable, and aligned with strategic goals.</li><li>
Lead future-forward AI/ML research, proactively identifying emerging techniques, publishing influential work, and filing patents to amplify Visa&rsquo;s innovation footprint.</li><li>
Integrate models into production with engineering and product teams, building robust, compliant pipelines with an eye on velocity, reliability, and business outcomes.</li><li>
Mentor scientists using Generative AI tools, cultivating technical depth, research excellence, and a culture of rigor and collaboration</li></ul><p>
This is a hybrid position. Expectation of days in office will be confirmed by your hiring manager.</p><b><br>
Qualifications</b><p><br>
Preferred Qualifications &ndash;</p><ul><li>
You have 7-10 years of work experience with a Bachelor&rsquo;s Degree or with an Advanced degree. PhD/MS in computer science, machine learning or related field preferred.</li><li>
Strong fundamentals in machine learning, deep learning, and optimization and solid understanding of the math behind them.</li><li>
You should be able to derive algorithms from first principles and understand their limitations.</li><li>
Proven track record of 6+ years of building AI / ML models which can handle scale (think model size, latency, architecture etc.,).</li><li>
You&rsquo;ve shipped models that matter, ideally in production environments with real users and measurable impact.</li><li>
You have deep technical and domain expertise in at least two domains where you are able to connect different ML techniques (e.g. contrastive learning, domain adaptation, etc.) to appropriate business problems.</li><li>
Fluency in code, you write clean, efficient Python, and you&rsquo;re comfortable navigating large codebases.</li><li>
You treat code as a medium for clarity and experimentation. You have experience in PySpark, PyTorch, tensor flow, as well as GPU based compute environments.</li><li>
Research mindset with product intuition. You know when to read papers and when to write them.</li><li>
You can balance novelty with practicality and know how to translate ideas into working systems.</li><li>
You are deeply technical covering both ML as well as deep learning fundamentals spanning design, pre-training, fine-tuning, and evaluation.</li><li>
Ownership and velocity. You take initiative, move fast, and iterate. You don&rsquo;t wait for permission, you define the problem, build the solution, and drive it to completion.</li><li>
Communication clarity. You can explain complex ideas simply, whether in a design doc, a pull request, or a hallway conversation. You write well and think clearly.</li></ul><br>
<b>
Additional Information</b><p><br>
Visa is an EEO Employer. Qualified applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, sexual orientation, gender identity, disability or protected veteran status. Visa will also consider for employment qualified applicants with criminal histories in a manner consistent with EEOC guidelines and applicable local law.</p></div>

Staff ML Scientist (7-10 years' experience)

New York University Abu Dhabi

<div>
 The Micro- and Nanoscale Bioengineering Lab (MNBL) at New York University Abu Dhabi is seeking to recruit a research assistant to study various human diseases using an organ/organoid-on-a-chip approach. Applicants with a strong background in designing and fabricating microfluidic devices and cell culture are encouraged to apply.
 <br/>
 <br/>
 Research in the MNBL focuses on designing and fabricating microphysiological systems to study various diseases affecting multiple human organs in vitro. Our project involves collaborations with the faculty of Bioengineering and Biology at NYUAD. Responsibilities of the position include growing cells in organ-on-a-chip microfluidic devices, characterizing them using downstream analysis such as bioimaging and omics analysis, and testing new potential drugs on these cells. The candidate will work in a multidisciplinary environment comprising PhD-level scientists, graduate students, and undergraduate students, thereby acquiring valuable skills in writing manuscripts and establishing collaborations across disciplines.
 <br/>
 <br/>
 Applicants must hold a B.S. degree in the engineering field. They must also have excellent cell biology expertise; multi-year experience of handling cells with microfluidic devices is essential.
 <br/>
 <br/>
 The terms of employment are very competitive and include housing and educational subsidies for children. Applications will be accepted immediately, and candidates will be considered until the position is filled.For consideration, applicants must submit a cover letter, a curriculum vitae with a full publication list, a statement of research interests, transcript and two letters of reference, all in PDF format. If you have any questions, please email Prof. Rafael Song at rafael.song@nyu.edu/.
 <br/>
 <br/>
 <strong>
  About NYU Abu Dhabi
  <br/>
  <br/>
 </strong>
 https://nyuad.nyu.edu/en/
 <br/>
 <br/>
 NYU Abu Dhabi is the first comprehensive liberal arts and research campus in the Middle East to be operated abroad by a major American research university. Times Higher Education ranks NYU among the top 30 universities in the world, making NYU Abu Dhabi the highest-ranked university in the UAE and MENA region. NYU Abu Dhabi has integrated a highly selective undergraduate curriculum across the disciplines with a world center for advanced research and scholarship. The university enables its students in the sciences, engineering, social sciences, humanities, and arts to succeed in an increasingly interdependent world and advance cooperation and progress on humanity&rsquo;s shared challenges. NYU Abu Dhabi&rsquo;s high-achieving students have come from over 120 countries and speak over 100 languages. Together, NYU's campuses in New York, Abu Dhabi, and Shanghai form the backbone of a unique global university, giving faculty and students opportunities to experience varied learning environments and immersion in other cultures at one or more of the numerous study-abroad sites NYU maintains on six continents.
 <br/>
 <br/>
 NYUAD is committed to upholding a culture of non-discrimination, anti-harassment, dignity, and mutual respect; providing equal access and opportunity; and fostering academic excellence in learning, research, and teaching.
 <br/>
 <br/>
 UAE Nationals are encouraged to apply
 <br/>
 <br/>
 <strong>
  Equal Employment Opportunity Statement
  <br/>
  <br/>
 </strong>
 <strong>
  For people in the EU, click here for information on your privacy rights under GDPR: www.nyu.edu/it/gdpr
  <br/>
  <br/>
 </strong>
 NYU is an Equal Opportunity Employer and is committed to a policy of equal treatment and opportunity in every aspect of its recruitment and hiring process without regard to age, alienage, caregiver status, childbirth, citizenship status, color, creed, disability, domestic violence victim status, ethnicity, familial status, gender and/or gender identity or expression, marital status, military status, national origin, parental status, partnership status, predisposing genetic characteristics, pregnancy, race, religion, reproductive health decision making, sex, sexual orientation, unemployment status, veteran status, or any other legally protected basis. All interested persons are encouraged to apply for vacant positions at all levels.
 <br/>
 <br/>
 <strong>
  Sustainability Statement
  <br/>
  <br/>
 </strong>
 NYU aims to be among the greenest urban campuses in the country and carbon neutral by 2040. Learn more at nyu.edu/sustainability
</div>


Junior Research Scientist in the Division of Engineering (MNBL) - Dr. Rafael Song

Indiana University

<p></p><div><div><div><div><div><div>The IU School of Medicine (IUSM) Department of Neurology is seeking well-qualified and highly motivated applications for a scientist track faculty position. All academic ranks (Assistant to Full Professor) will be considered. Applications will be reviewed on an ongoing basis; start dates are flexible. The successful applicant will be a Ph.D. scientist responsible for management and conduct of laboratory projects under the guidance of Senior Research Professor of Neurology, Dr. Jeffrey Dage.
<br>
<br>
IU School of Medicine is committed to being a welcoming campus community and we seek candidates whose research, teaching, and community engagement efforts contribute to robust learning and working environments for all students, staff, and faculty. We invite individuals who will join us in our mission to improve health equity and well-being for all throughout the state of Indiana.<br>
<br>
Indianapolis is the capital and most populous city in the State of Indiana. It is growing economically thanks to a strong corporate base anchored by the life sciences. Indiana is home to one of the nation&rsquo;s largest concentrations of health sciences companies. Indianapolis has a sophisticated blend of charm and culture with a wonderful balance of business and leisure. The growing residential base is supported by rich amenities and quality of life &ndash; the city possesses a variety of professional sports, arts venues, and outdoor recreation areas. Residents of this dynamic city and surrounding suburbs enjoy leading educational systems and top-ranked universities paired with a diverse population. Indianapolis International Airport is a top-ranked international airport that has been named &ldquo;Best Airport in North America&rdquo; by Airports Council International for many years. For additional information on life in Indy: <b>https://faculty.medicine.iu.edu/relocation</b>
</div>
</div><br>
<div><div><b>Basic Qualifications</b></div>
<div>Doctorate or terminal degree required. Successful applicants must have PhD and/or MD degree.</div>
</div><br>
<div><div><b>Department Contact for Questions</b></div>
<div>Dr. Jeffrey Dage<br>
jdage@iu.edu</div>
</div><br>
<div><div><b>Additional Qualifications</b></div>
</div><br>
<div></div><div><div><b>Special Instructions</b></div>
</div><br>
<div></div><div><div><b>Priority Application Review Deadline</b></div>
</div><br>
<div></div><div><div><b>Expected Start Date</b></div> <div>11/01/2025</div>
</div><br>
<div><div><b>Posting Number</b></div> <div>IUSM-02280-2025</div></div></div></div></div></div>

Assistant/Associate/Full Research Professor of Neurology

Yum! Brands

<div>
 <strong>
  KRA
  <br/>
  <br/>
  <br/>
 </strong>
 <ul>
  <li>
   Become an expert in Kvantum marketing analytics platform to perform statistical analysis and modeling as well as engage with Kvantum data science, marketing science &amp; product dev teams to deliver end to end MMM (&ldquo;Marketing Mix Modeling&rdquo;) engagements.
  </li>
  <li>
   Leverage understanding of statistical techniques and hypothesis development to design tests/ experiments, analyze data, draw conclusions with actionable recommendations to help Yum! it's Brands &amp; Franchisees, and external Fortune 100 companies with data driven decision making.
  </li>
  <li>
   Understand the outcomes of complex MMM and attribution models (AI/machine learning) to support Yum! And external stakeholders along with their media agencies in building strategic media plans.
  </li>
  <li>
   Build powerful brand story using models with business &amp; technology context, latest marketing activities in real-world.
  </li>
  <li>
   Generate predictive models and optimization scenarios to support budget planning.
   <br/>
   <br/>
   <br/>
  </li>
 </ul>
 <strong>
  Key Skills
  <br/>
  <br/>
  <br/>
 </strong>
 <ul>
  <li>
   Master&rsquo;s degree with 3+ years of experience in business analytics OR bachelor&rsquo;s degree with 4.5+ years of management consulting experience with top tier companies.
  </li>
  <li>
   Good understanding of the statistical models &amp; variables typically used in marketing, customer, category, and/or pricing analytics.
  </li>
  <li>
   Tell a data informed story leveraging MS Power point.
  </li>
  <li>
   Analyze data leveraging various tools - MS Excel, SQL, and/or Python
  </li>
  <li>
   Deliver recommendations to senior leadership.
   <br/>
   <br/>
   <br/>
  </li>
 </ul>
 Note: Apart from &ldquo;must haves&rdquo;, If you understand any of these (QSR, CPG, Retail, Aggregators) domains at deeper level and/or you have a knack to analyze any business leveraging data, it will set you apart.
 <br/>
 <br/>
 The Yum! Brands story is simple. We have the four distinctive, relevant and easy global brands &ndash; KFC, Pizza Hut, Taco Bell and The Habit Burger Grill -- born from the hopes and dreams, ambitions and grit of passionate entrepreneurs. And we want more of this to create our future!
 <br/>
 <br/>
 As the world&rsquo;s largest restaurant company we have a clear and compelling mission: to build the world&rsquo;s most love, trusted and fastest-growing restaurant brands. The key and not-so-secret ingredient in our recipe for growth is our unrivaled talent and culture, which fuels our results.
 <br/>
 <br/>
 We&rsquo;re looking for talented, motivated, visionary and team-oriented leaders to join us as we elevate and personalize the customer experience across our 48,000 restaurants, operating in 145 countries and territories around the world!
 <br/>
 <br/>
 We put pizza, chicken and tacos in the hands of customers through customized ordering, unique delivery approaches, app experiences, and click and collect services and consumer data analytics creating unique customer dining experiences &ndash; and we are only getting started.
 <br/>
 <br/>
 Employees may work for a single brand and potentially grow to support all company-owned brands depending on their role. Regardless of where they work, as a company opening an average of 8 restaurants a day worldwide, the growth opportunities are endless. Taco Bell has been named of the 10 Most Innovative Companies in the World by Fast Company; Pizza Hut delivers more pizzas than any other pizza company in the world and KFC&rsquo;s still use its 75-year-old finger lickin&rsquo; good recipe including secret herbs and spices to hand-bread its chicken every day.
 <br/>
 <br/>
 Yum! and its brands have offices in Chicago, IL, Louisville KY, Irvine, CA, Plano, TX and other markets around the world. We don&rsquo;t just say we are a great place to work &ndash; our commitments to the world and our employees show it. Yum! has been named to the Dow Jones Sustainability North America Index and ranked among the top 100 Best Corporate Citizens by Corporate Responsibility Magazine in addition to being named to the Bloomberg Gender-Equality Index. Our employees work in an environment where the value of &ldquo;believe in all people&rdquo; is lived every day, enjoying benefits including but not limited to: 4 weeks&rsquo; vacation PLUS holidays, sick leave and 2 paid days to volunteer at the cause of their choice and a dollar-for-dollar matching gift program; generous parental leave; competitive benefits including medical, dental, vision and life insurance as well as a 6% 401k match &ndash; all encompassed in Yum!&rsquo;s world-famous recognition culture.
</div>


Lead- Marketing Scientist - MMM

Search 10000+ Md senior research scientist jobs near you this November. New roles added regularly across leading industries. Apply today.

10000 md senior research scientist jobs NEAR_ME

Sr. Applied Scientist , AMX Science

Postdoctoral Appointee - MSD Computational Materials

Staff ML Scientist (7-10 years' experience)

Junior Research Scientist in the Division of Engineering (MNBL) - Dr. Rafael Song

Junior Research Scientist in the Division of Engineering (MNBL) - Dr. Rafael Song

Assistant/Associate/Full Research Professor of Neurology

Lead- Marketing Scientist - MMM