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Gan Jobs (NOW HIRING)

Gan & Lee Pharmaceuticals

The position will work with Gan & Lee clinical program lead(s) to provide the scientific and clinical leadership and inputs in meeting the development objectives for the program.Education and ...

Qorvo, Inc.

Sr Principal GaN Scientist

Richardson, TX · On-site

Extensive hands-on experience in developing and releasing advanced device technologies, particularly GaN , with complementary expertise in GaAs , InP , and other compound semiconductors. * Cross ...

Qorvo, Inc.

Sr Principal GaN Scientist

Richardson, TX · On-site

Extensive hands-on experience in developing and releasing advanced device technologies, particularly GaN , with complementary expertise in GaAs , InP , and other compound semiconductors. * Cross ...

Power Integrations

Staff Device Engineer

San Jose, CA · On-site

Design and qualify high-voltage GaN power devices integrated in high performance and high reliability products (including automotive). * Perform device/process simulations and device layout for GaN ...

Power Integrations

Staff Device Engineer

San Jose, CA · On-site

Design and qualify high-voltage GaN power devices integrated in high performance and high reliability products (including automotive). * Perform device/process simulations and device layout for GaN ...

Power Integrations

Staff Device Engineer

San Jose, CA · On-site

Design and qualify high-voltage GaN power devices integrated in high performance and high reliability products (including automotive). * Perform device/process simulations and device layout for GaN ...

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Gan information

What are some common challenges faced by GAN researchers or engineers in industry roles?

Professionals working with GANs often encounter challenges such as training instability, mode collapse, and the need for large, high-quality datasets. GANs require careful tuning of hyperparameters and regular troubleshooting to balance the generator and discriminator, which can be time-consuming. Collaboration with data scientists, software engineers, and domain experts is typical to refine models and deploy them in production, and staying updated with the latest research is key to overcoming technical hurdles.

What is the difference between Gan vs Machine Learning Engineer?

AspectGanMachine Learning Engineer
Required CredentialsTypically a degree in computer science, AI, or related fields; experience with deep learning frameworksSimilar credentials; often requires knowledge of algorithms, programming, and data analysis
Work EnvironmentResearch labs, AI startups, tech companies focusing on generative modelsTech companies, data-driven organizations, AI departments across industries
Industry UsagePrimarily in AI research, generative modeling, and creative applicationsBroader industry applications including predictive modeling, data analysis, and automation

Gan (Generative Adversarial Network) specialists focus on developing generative models for creating new data, images, or content. Machine Learning Engineers work on designing, implementing, and optimizing various machine learning models across multiple applications. While both roles require a strong background in AI and programming, Gans are more specialized in generative modeling, whereas Machine Learning Engineers have a broader scope in deploying and maintaining machine learning solutions.

What is a GAN?

GANs, or Generative Adversarial Networks, are a class of machine learning frameworks where two neural networks, called the generator and discriminator, are trained together in a competitive setting. The generator creates data samples that mimic real data, while the discriminator evaluates whether samples are real or generated. This process helps GANs learn to produce highly realistic data, such as images, videos, or audio, making them popular in applications like image synthesis, data augmentation, and creative AI tasks. GANs have become an important tool in artificial intelligence and deep learning research.

What are the key skills and qualifications needed to thrive as a GAN engineer, and why are they important?

To thrive as a GAN Engineer, you need a strong background in machine learning, deep learning, and mathematics, typically supported by a degree in computer science or a related field. Expertise in frameworks such as TensorFlow or PyTorch, and experience with programming languages like Python, are essential, along with familiarity with GAN architectures. Creativity, strong problem-solving skills, and effective communication help distinguish top performers in this role. These abilities are critical for developing, optimizing, and explaining innovative generative models that advance AI capabilities.
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Infographic showing various Gan job openings in the United States as of August 2026, with employment types broken down into 98% Full Time, 1% Part Time, and 1% Contract. Highlights an 92% Physical, 4% Hybrid, and 4% Remote job distribution.

Senior Manager, Clinical Scientist

Gan & Lee Pharmaceuticals

Remote

Full-time

Re-posted 23 days ago

Job description

SummaryThis position reports to the Head of Clinical Development at Gan & Lee Pharmaceuticals USA Corporation or designee. The position will work with Gan & Lee clinical program lead(s) to provide the scientific and clinical leadership and inputs in meeting the development objectives for the program.Education and Credentials
  • Medical Degree, PhD, or PharmD.
Experience
  • At least 2-4 years in clinical development experiences at a pharmaceutical, biotechnology, CRO company, clinical training/practice, and/or academia.
  • Experiences in metabolic diseases (Diabetes, Obesity, NASH, NAFLD, etc.), Endocrinology (CKD, CRF, etc.), and Nutrition and Weight Management related drug development are a plus.
  • Board eligibility or certification preferred
Skills
  • Demonstrated ability to manage multiple and diverse projects concurrently.
  • Demonstrated ability to develop positive relationships and collaborations.
  • Strong analytical skills; a strategic thinker, planner, and implementer.
  • Solid scientific skills and attentive to details.
  • Working knowledge of biostatistics is a plus.
  • Ability to operate independently with minimal supervision.
  • Deep experience with literature analysis, proven technical English writing skills.
  • Excellent written and oral communicator in English.
  • Strong proficiency in major Microsoft Office products (i.e., Word, Excel, PowerPoint, Project).
  • Enthusiastic, genuine, ethical, fair, and loyal to the organization and its vision and goals.
Responsibilities
  • Provides scientific and/or medical expertise for clinical research aspects of the project.
  • Participates in strategic meetings/advisory boards as key clinical research representative.
  • Provides medical and scientific input to the core documents for the project (e.g., product strategy documents, target product profile (TPP), protocols, submission, etc.).
  • Consults with internal/external stakeholders and internal/external key opinion leaders.
  • Provides support to other functional members of the project team.
  • Interacts with investigators and CROs as the medical or scientific representative.
  • Provides medical and scientific interpretation of efficacy and safety data.
  • Participates in the interactions with regulatory authorities (e.g., FDA, EMEA meetings). This includes developing key documents, participating in the preparation for meetings with the health authorities, and participating in the meetings and interactions with the health authorities. 
  • Provides input for a project publication plan, liaises with commercial and works on launch activities when required.
  • Creates and reviews abstracts, and manuscripts created by internal or external sources.

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