Responsibilities:

1. Develop computational workflows to support cutting-edge research in chemistry and materials science.
2. Collaborate with cloud and software engineers to design robust data infrastructures
and workflows tailored for chemistry and materials applications.
3. Partner with internal business and technical teams to identify and address emerging
computational needs.
4. Work closely with enterprises and clients to drive industry breakthroughs.

Requirements:

1. Research experience in computational chemistry and materials (e.g., proficiency with
quantum chemistry software like PySCF, Orca). A Master’s degree or higher in materials
science, chemistry, chemical engineering, physics, or a related field is required.
Industry experience is a plus.
2. Strong understanding of chemistry or materials science. Experience with computational
workflows (e.g., FireWorks, AiiDA, Atomate) for catalytic research is preferred.
3. Excellent problem-solving skills, with the ability to independently research
scientific or industrial problems.
4. Proficiency in programming languages such as Python or C++, with strong algorithm
development and implementation capabilities.
5. Interdisciplinary collaboration skills, with the ability to effectively communicate
technical concepts to non-specialists. A growth mindset and commitment to solving
critical scientific discovery challenges through technology.

Preferred Qualifications:

1. Experience building deep learning pipelines, particularly for molecular and materials
design (e.g., GuacaMol, Open Catalyst Project).
2. Hands-on experience with cloud infrastructure and development (e.g., Docker,
Kubernetes, containerization).
3. Startup or entrepreneurial experience is a significant advantage.

Responsibilities:

1. Develop and apply cutting-edge deep learning models to drive innovation in chemistry
and materials science.
2. Design, develop, and maintain machine learning pipelines focused on chemical and
material data, including data collection, preprocessing, feature engineering, model
training, and evaluation.
3. Collaborate closely with cloud and software engineers to design and implement data
infrastructure and workflows centered on chemistry and materials.
4. Work with internal business and technical teams to understand business requirements
and apply machine learning technologies to solve real-world problems, driving commercial
value.
5. Stay at the forefront of machine learning advancements, applying the latest research
outcomes to projects and continuously improving team expertise.

Requirements:

1. Master’s degree or higher in a relevant field (e.g., Chemistry, Computer Science,
Materials Science) with experience in deep learning.
2. Proficiency in at least one deep learning framework (e.g., TensorFlow, PyTorch) with
substantial experience in model development.
3. Strong understanding of machine learning algorithms and theories, particularly in
deep learning areas such as Graph Neural Networks (GNNs), Recurrent Neural Networks
(RNNs), and Convolutional Neural Networks (CNNs).
4. Excellent programming skills in Python or C++, with strong algorithm development and
implementation capabilities.
5. Strong sensitivity to data, with experience in data cleaning, preprocessing, and
feature engineering, as well as extracting valuable insights from data.
6. Passion for AI for Science, with a commitment to advancing chemistry and materials
science through AI technologies.

Preferred Qualifications:

1. Familiarity with chemistry and materials science. Machine learning experience related
to molecules, proteins, or materials is highly valued.
2. Experience with cloud computing platforms (e.g., AWS, Azure, GCP) and
containerization technologies (e.g., Docker, Kubernetes).
3. Experience in developing large-scale software projects, with knowledge of version
control systems (e.g., Git) and code testing processes.
4. Startup or entrepreneurial experience is a strong plus.

Responsibilities:

1. Develop and implement comprehensive business development strategies to support the
company’s overarching goals.
2. Identify, develop, and manage potential clients and partners in industries such as
chemical materials, pharmaceutical intermediates, synthetic biology, and related fields.
3. Build and strengthen relationships with key decision-makers at potential clients and
partners.
4. Oversee negotiation processes to ensure contracts align with business and financial
objectives.
5. Continuously monitor industry trends and competitive dynamics, proactively
identifying new business opportunities and partnerships.

Requirements:

1. 5-10+ years of business development experience, with preference for candidates with
expertise in chemical materials, pharmaceutical intermediates, synthetic biology, AI, or
industrial digitization.
2. Proven experience in developing, maintaining, and managing strategic partnerships.
3. In-depth understanding of B2B sales cycles and the ability to handle complex sales
processes.
4. Exceptional communication, interpersonal, and presentation skills.
5. Self-motivated, results-oriented, and capable of building trust and rapport with
stakeholders.

Preferred Qualifications:

1. Startup or entrepreneurial experience is highly valued.
2. Deep understanding of AI and machine learning applications in biopharma and materials chemistry.