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Biomolecular Jobs (NOW HIRING)

Waters Corporation

Sr Scientist

Milford, MA · On-site

$100K - $137K/yr

Expertise in biomolecular interactions, such as the protein-protein interactions or biomolecule-to-surface interactions is desired. * Experience with different solid surface bioconjugation approaches ...

Waters Corporation

Sr Scientist

Milford, MA · Hybrid

$100K - $137K/yr

Expertise in biomolecular interactions, such as the protein-protein interactions or biomolecule-to-surface interactions is desired. * Experience with different solid surface bioconjugation approaches ...

Waters Corporation

Sr Scientist

Milford, MA · Hybrid

$100K - $137K/yr

Expertise in biomolecular interactions, such as the protein-protein interactions or biomolecule-to-surface interactions is desired. * Experience with different solid surface bioconjugation approaches ...

Harvard University

Postdoctoral Fellow

Cambridge, MA · On-site

$54K - $73K/yr

Biomolecular condensates; G-protein-coupled receptors (GPCRs); Cell and molecular biology -Cryo-vitrification via cryo-plunging and high-pressure freezing; Time-resolved freezing -Microfluidics ...

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Biomolecular information

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$74K

$152.7K

$300K

How much do biomolecular jobs pay per year?

As of Jun 23, 2026, the average yearly pay for biomolecular in the United States is $152,666.00, according to ZipRecruiter salary data. Most workers in this role earn between $111,500.00 and $180,000.00 per year, depending on experience, location, and employer.

What biology jobs pay over $100k?

Biomolecular scientists and related roles such as senior research scientists, biotechnologists, and molecular biologists often earn over $100,000 annually, especially with advanced degrees and experience. Positions in pharmaceutical, biotech, and research industries, as well as roles involving management or specialized skills like bioinformatics, tend to have higher salaries. Certifications, publication records, and expertise in laboratory techniques can also influence earning potential.

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

To thrive as a Biomolecular Scientist, a solid background in molecular biology, biochemistry, and genetics, often supported by at least a bachelor's or master's degree in a life science field, is essential. Familiarity with laboratory techniques such as PCR, gel electrophoresis, and use of bioinformatics tools, as well as experience with laboratory information management systems (LIMS), is typically required. Attention to detail, strong analytical thinking, and effective collaboration skills help individuals excel in both independent research and team-based projects. These competencies are crucial for ensuring accurate experiments, reliable data interpretation, and successful progress in biomolecular research and development.

What are 5 careers in biotechnology?

Biomolecular careers in biotechnology include roles such as research scientist, bioinformatics analyst, laboratory technician, quality control specialist, and bioprocess engineer. These positions often require knowledge of molecular biology techniques, laboratory skills, and familiarity with biotech tools and equipment.

What jobs pay 10,000 a month without a degree?

Biomolecular roles typically require specialized education or training; however, high-paying jobs without a degree are rare. Some options include sales positions, technical trades, or entrepreneurship, which may reach or exceed $10,000 monthly with experience and skill. Success often depends on industry, location, and individual performance.

What are biomolecular scientists?

Biomolecular scientists are professionals who study the structure, function, and interactions of biological molecules such as proteins, nucleic acids, carbohydrates, and lipids. They use advanced laboratory techniques to understand how these molecules contribute to the processes of life, including health, disease, and cellular functions. Biomolecular scientists work in various fields, including biotechnology, pharmaceuticals, healthcare, and academic research, often contributing to discoveries in medicine, genetics, and environmental science.

What can you do with a biomolecular degree?

A biomolecular degree prepares individuals for careers in research, biotechnology, pharmaceuticals, and healthcare, involving tasks such as laboratory analysis, data interpretation, and product development. Graduates often work as research scientists, lab technicians, or quality control specialists, utilizing skills in molecular biology, biochemistry, and laboratory techniques. Advanced roles may require additional certifications or advanced degrees.

What are some common challenges faced by professionals working in biomolecular research, and how can they be overcome?

One common challenge in biomolecular research is keeping up with rapidly evolving technologies and methodologies. Researchers often need to continuously update their skills and knowledge to effectively analyze complex biological data and operate advanced laboratory equipment. Collaboration with interdisciplinary teams, such as bioinformaticians and chemists, is also essential, which requires strong communication and project management skills. To overcome these challenges, professionals are encouraged to participate in ongoing training, attend conferences, and actively engage in cross-functional projects within their organizations.

What is the difference between Biomolecular vs Biochemist?

AspectBiomolecularBiochemist
Required CredentialsBachelor's or Master's in biology, biochemistry, or related fieldsBachelor's or Master's in biochemistry, chemistry, or related fields
Work EnvironmentLaboratories, research facilities, biotech companiesLaboratories, pharmaceutical companies, research institutions
Industry UsageBiotechnology, pharmaceuticals, academiaPharmaceuticals, research, academia
Common Search/ComparisonBiomolecularBiochemist

Biomolecular professionals focus on studying and manipulating biological molecules like proteins and nucleic acids, often working in biotech and research settings. Biochemists also study biological molecules but may have a broader focus on chemical processes within living organisms. Both roles require similar educational backgrounds and often overlap in research environments, but their specific applications and focus areas differ slightly.

More about Biomolecular jobs
What states have the most Biomolecular jobs? States with the most job openings for Biomolecular jobs include:
What job categories do people searching Biomolecular jobs look for? The top searched job categories for Biomolecular jobs are:
Biomolecular jobs near you
Infographic showing various Biomolecular job openings in the United States as of June 2026, with employment types broken down into 91% Full Time, 8% Part Time, and 1% Temporary. Highlights an 86% Physical, 2% Hybrid, and 12% Remote job distribution, with an average salary of $152,666 per year, or $73.4 per hour.

ML Research Scientist - Atomistic Simulation Models

Achira

New York, NY • On-site

$164K - $259K/yr

Full-time

Posted 2 days ago

Job description

Invent and exploit probabilistic generative models that exploit to Achira's foundation simulation models for drug discovery to accelerate generative molecular design and biomolecular conformational sampling.
Why Achira
  • Join a world-class team of researchers, scientists, and engineers unifying probabilistic AI/ML and molecular simulation to reimagine small molecule drug discovery.
  • Advance new architectures for conditional 3D generation and learned proposal mechanisms informed by physical priors.
  • Operate at the frontier scale of large models, large datasets, and high-throughput evaluation on an ML-framework-native biomolecular simulation stack.
  • Own impact end-to-end from model conception to sampler design to prospective design tools.
  • Work in a culture that rewards rigor, speed, and scientific depth with an ownership mindset.

About the Role
Achira is building foundation simulation models and conditional generators for molecular systems. You will design probabilistic generative models (utilizing strategies such as diffusion models, normalizing flows, and flow matching) that that exploit Achira's next-generation biomolecular simulation potentials. Your work will enable target- and property-conditioned small-molecule generation and efficient exploration of biomolecular conformational landscapes, driving measurable gains in efficiency for small molecule design.
Familiarity with statistical mechanics-particularly nonequilibrium statistical mechanics based on Crooks/Jarzynski viewpoints-is desirable, but the center of gravity is probabilistic AI/ML.
What You'll Do
  • Develop conditional molecular generators: Build conditional small-molecule generators (e.g., pocket/scaffold/pharmacophore- and property-conditioned) using generative modeling strategies such as diffusion models, normalizing flows, and flow matching with 3D- and symmetry-aware representations.
  • Develop efficient samplers: Develop sequential sampling pipelines (e.g. SMC/AIS/tempering/Boltzmann generators) that anneal from learned priors into probabilities induced by Achira's ML potentials, maximizing ESS and reducing bias/variance.
  • Couple learning and sampling: Design learned proposal mechanisms (transport maps, score-guided moves) that adapt to stiff, multimodal landscapes and improve mixing and wall-clock efficiency.
  • Leverage nonequilibrium statistical mechanics: Where beneficial, use nonequilibrium switching protocols and work-based estimators to accelerate exploration and estimate partition-function ratios/affinity proxies.
  • Measure what matters: Define and track relevant metrics (ESS/compute, acceptance probabilities) and build reliable evaluation harnesses for fast, physics-informed feedback.
  • Experiment and engineer for reproducibility: Collaborate with our engineering team to implement robust research software in Python (PyTorch and/or JAX), with tests, CI, experiment tracking, and clear documentation.
  • Collaborate closely: Partner with computational chemistry, AI/ML, and platform teams to shape objectives (potency, selectivity, developability) and run prospective design studies.
  • Automate workflows: Use generative coding and experiment-management tools to accelerate iteration and close active-learning loops with synthetic data generation in the loop.

About You
  • Probabilistic ML background: Deep grasp of probabilistic machine learning, Markov chain Monte Carlo, variational inference, diffusion models, normalizing flows, flow matching, and uncertainty quantification.
  • Sequential methods expert: Experience with sequential Monte Carlo methods, proposal design, and diagnostics for high-dimensional, multimodal targets.
  • Geometric intuition: Comfort with graph/point-cloud/SE(3)-aware models and constraints relevant to protein-ligand systems and conformer generation.
  • Systems thinker: You integrate models into end-to-end pipelines (data → model → sampler → physics-aware evaluation → candidate triage) and care about measurable impact.
  • Familiarity with statistical mechanics(nice to have): Working knowledge of statistical mechanics, sampling, estimators, and the Crooks/Jarzynski perspective of nonequilibrium statistical mechanics will be a superpower.
  • Engineering discipline: Strong Python skills with PyTorch and/or JAX, Git/CI/testing, and reproducible experiment management.
  • Mindset: You value rigor, move with urgency, collaborate well, and enjoy turning ideas into reliable, high-impact tools.

• Minimum Qualifications
  • PhD (or equivalent research experience) in computer science, statistics, applied math, computational chemistry/biology, or related field.
  • Demonstrated track record in probabilistic ML and generative modeling (publications, impactful open-source, or deployed systems).
  • Industry experience tackling practical machine learning problems.
  • Hands-on experience with diffusion/flows/flow matching on structured or geometric data.
  • Practical experience with sequential Monte Carlo/AIS/tempering and/or advanced MCMC.
  • Proficiency in Python with PyTorch and/or JAX; strong software engineering hygiene.
  • Familiarity with biomolecular structure and data representations (graphs/3D/SMILES).

☆ Preferred Qualifications
  • Experience with ML interatomic/energy potentials is a bonus
  • Background in SE(3)-equivariant architectures, geometric deep learning, or score matching on manifolds.
  • Experience with active learning / Bayesian optimization or RL-style acquisition for proposal selection.
  • Experience with implementing MCMC sampling approaches grounded in statistical mechanics-especially nonequilibrium approaches that utilize Crooks/Jarzynski-a plus.
  • Contributions to open-source scientific software; experience mentoring or leading small research efforts.
Eligibility
In compliance with United States federal law, all persons hired will be required to verify identity and eligibility to work in the United States and to provide required employment eligibility verification documentation upon hire.

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